Vocabulary | Corpus Linguistics — How Real Language Data Reveals Frequency, Collocations and Word Use

1. What a Corpus Is

A corpus is a collection of naturally occurring or systematically gathered language assembled for analysis. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

2. What Corpus Linguistics Does

Corpus linguistics studies patterns of language use by examining evidence across collections rather than relying only on individual intuition. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

3. Why Corpora Matter for Vocabulary

Vocabulary is distributional: words differ in frequency, context, register, phrase partners and genre. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

4. Real Language Data

Corpus examples come from language that was actually written or spoken in particular contexts. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

5. Representativeness

A corpus should represent the language variety or domain relevant to the question being asked. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

6. Balance

Balanced corpora sample multiple genres or contexts so one domain does not dominate the evidence unintentionally. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

7. Specialised Corpora

A specialised corpus focuses on one domain such as medicine, law, education, engineering, finance or academic writing. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

8. General Corpora

General corpora aim to cover a wider range of language use and support broad vocabulary questions. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

9. Written Corpora

Written corpora can include fiction, news, essays, academic articles, web pages, reports and other text genres. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

10. Spoken Corpora

Spoken corpora represent conversation, interviews, lectures, meetings or other transcribed speech. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

11. Learner Corpora

Learner corpora collect language produced by learners and make developmental patterns or recurring errors visible. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

12. Parallel Corpora

Parallel corpora align translated texts across languages and help compare lexical choices and translation patterns. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

13. Comparable Corpora

Comparable corpora contain similar genres or domains across languages or varieties without requiring sentence-by-sentence translation alignment. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

14. Historical Corpora

Historical corpora allow researchers to trace how vocabulary frequency, meaning and phraseology change over time. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

15. Monitor Corpora

Monitor corpora are continually updated and can reveal emerging vocabulary and changing usage. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

16. Corpus Size

Larger corpora provide more evidence for rare items, though size alone does not guarantee relevance or quality. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

17. Corpus Design

The design should fit the question; a massive social-media corpus may be poor evidence for formal academic writing. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

18. Corpus Metadata

Metadata such as date, genre, speaker, region or discipline allows vocabulary patterns to be compared across contexts. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

19. Tokens

Tokens are occurrences of running words or other defined units in a corpus. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

20. Types

Types are distinct forms within a sample, useful for describing lexical variety but sensitive to tokenisation decisions. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

21. Lemmas

Lemma-based analysis groups inflectional forms under a dictionary-like headword for many frequency questions. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

22. Word Families

Family-based analysis can group derivational relatives more broadly, but assumptions about learner accessibility must remain explicit. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

23. Tokenisation

Tokenisation decides how running text is divided into units, which affects counts of punctuation, contractions, compounds and multiword expressions. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

24. Normalisation

Frequency counts are often normalised to a common base so corpora of different sizes can be compared. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

25. Raw Frequency

Raw frequency is the number of times an item occurs in the corpus. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

26. Relative Frequency

Relative frequency adjusts counts to corpus size and supports fairer comparison. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

27. Frequency Lists

Frequency lists rank items by occurrence and help identify common vocabulary. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

28. High-Frequency Vocabulary

High-frequency words provide broad coverage across many texts and often deserve early instructional priority. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

29. Mid-Frequency Vocabulary

Mid-frequency vocabulary becomes increasingly important as learners move into wider reading and academic domains. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

30. Low-Frequency Vocabulary

Low-frequency words can be crucial in specialist fields even when they are rare in general corpora. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

31. Frequency Is Domain-Dependent

A word can be rare generally but extremely common inside medicine, computing or another specialised field. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

32. Dispersion

Dispersion measures how widely an item occurs across texts or corpus sections rather than merely how many times it appears. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

33. Why Dispersion Matters

A word occurring 1,000 times in one document is different from a word occurring across hundreds of documents. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

34. Range

Range counts how many texts, genres or subcorpora contain an item and complements raw frequency. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

35. Zipfian Distributions

Language frequency is highly skewed: a small set of words occurs very often while many words are rare. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

36. Frequency Bands

Frequency bands group vocabulary into ordered ranges that can support teaching, profiling and coverage analysis. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

37. Concordance

A concordance displays occurrences of a search item with surrounding context. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

38. KWIC

Key Word in Context aligns the search word centrally so recurring patterns become easier to scan. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

39. Concordance Lines

Multiple concordance lines let learners compare many real examples quickly. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

40. Sorting Concordances

Sorting by words to the left or right can expose recurring grammatical and lexical patterns. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

41. Collocation

Corpus tools identify words that occur near a target more often or more prominently than expected. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

42. Collocate Window

A collocation window defines how many words to the left or right are included in the analysis. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

43. Association Measures

Statistical association measures help distinguish frequent co-occurrence from combinations that are unusually strong relative to chance. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

44. Mutual Information

Mutual information can highlight distinctive associations but may overemphasise rare combinations if interpreted without frequency. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

45. T-Score and Related Measures

Frequency-sensitive statistics can favour common stable collocations and complement other association measures. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

46. No Single Best Collocation Statistic

Different measures answer different questions, so frequency, dispersion and qualitative inspection should accompany scores. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

47. N-Grams

N-grams are recurring sequences of a specified number of tokens. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

48. Clusters

Clusters are repeated word sequences that reveal phraseological patterns in a corpus. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

49. Lexical Bundles

Lexical bundles are frequent recurring multiword sequences characteristic of particular registers or genres. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

50. Formulaic Language

Corpus evidence shows that vocabulary knowledge includes recurring multiword sequences as well as individual words. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

51. Keywords

Keywords are items unusually frequent in one corpus relative to a reference corpus. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

52. Reference Corpus

A reference corpus supplies the comparison baseline for keyword analysis. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

53. Keyness

Keyness is statistical distinctiveness, not necessarily everyday importance or SEO-style keyword value. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

54. Positive Keywords

Positive keywords are overrepresented relative to the reference corpus. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

55. Negative Keywords

Negative keywords are underrepresented relative to the reference corpus and can be equally revealing. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

56. Keyword-in-Context Analysis

Keyword statistics should be followed by context inspection so the analyst understands what the item is doing. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

57. Semantic Preference

Corpus patterns can reveal recurring semantic classes around a word, such as types of problem, person or event. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

58. Semantic Prosody

Repeated contextual associations can give words evaluative tendencies not obvious from isolated definitions. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

59. Register

Corpus comparison can reveal whether a word or phrase is concentrated in conversation, news, academic prose or another register. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

60. Genre

Genre-specific distributions help learners avoid transferring a phrase from one discourse world into another without checking fit. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

61. Colligation

Colligation describes association between lexical items and grammatical patterns. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

62. Phraseology

Phraseology studies recurring multiword patterns, idioms, collocations and formulaic sequences. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

63. Word Sketches

Some corpus systems summarise a word’s frequent grammatical and collocational relations automatically. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

64. Thesaurus Functions

Distributional thesaurus tools identify words occurring in similar contexts, useful for candidate discovery but not guaranteed synonymy. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

65. Corpus Search Syntax

Search interfaces may support exact phrases, lemmas, part-of-speech tags, wildcards and proximity queries. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

66. Part-of-Speech Tagging

POS tags allow users to search grammatical categories rather than surface strings alone. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

67. Lemmatization

Lemmatization links inflectional variants so analysts can examine a broader lexical item. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

68. Annotation

Corpora may contain grammatical, semantic, discourse or speaker annotations that expand the kinds of vocabulary questions possible. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

69. Concordance Sampling

When thousands of results exist, random or systematic sampling can make qualitative analysis manageable. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

70. Corpus Bias

Every corpus reflects its sources, exclusions, time period and collection methods. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

71. Search-Engine Results Are Not a Corpus by Default

Web search counts are unstable and opaque; corpus methods require clearer data boundaries and procedures. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

72. Web as Corpus

Purpose-built web corpora can use large online datasets when sampling and processing are documented. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

73. Corpus Evidence vs Dictionary Evidence

Dictionaries curate lexical information; corpora expose distributions across many authentic contexts. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

74. Corpus Evidence vs Intuition

Intuition can generate hypotheses, while corpus evidence can confirm, complicate or reject them. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

75. Corpus Evidence vs Rules

Observed frequency does not automatically become a rule about what every learner must say. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

76. Descriptive vs Prescriptive Questions

Corpora describe documented usage; educational standards may additionally involve genre conventions and institutional expectations. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

77. Vocabulary Selection

Frequency, dispersion, learner need and domain value can work together when selecting words to teach. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

78. Vocabulary Prioritisation

High utility comes from a combination of occurrence, range, transfer potential and relevance rather than frequency alone. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

79. Vocabulary Size Research

Corpora provide frequency frameworks that support estimates of vocabulary breadth and lexical coverage. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

80. Lexical Coverage

Corpus-derived frequency information helps estimate how much vocabulary is needed to understand different text types. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

81. Lexical Profiling

Profiling tools compare a text’s vocabulary against frequency or reference lists. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

82. Collocation Learning

Corpus examples reveal the partners that make known words usable. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

83. Register Learning

Comparing subcorpora shows how the same word behaves differently across contexts. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

84. Academic Vocabulary

Academic corpora reveal words and phrases that recur across disciplines or within specialised fields. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

85. Professional Vocabulary

Specialised corpora help identify the lexical system of a workplace or profession. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

86. School Subject Vocabulary

Small subject corpora can expose recurrent terms, command words and phrase patterns in textbooks and exam materials. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

87. Reading

Corpus evidence helps teachers identify which words and phrases repeatedly shape a text domain. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

88. Writing

Writers can use corpora to test collocation, phrase frequency and genre fit. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

89. Speaking

Spoken corpora provide evidence about conversational vocabulary, discourse markers and common phraseology. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

90. Listening

Spoken-frequency evidence helps identify lexical items and chunks learners are likely to encounter in real speech. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

91. Vocabulary Assessment

Corpus-based item selection can make tests more representative of target language domains. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

92. Corpus-Informed Dictionaries

Modern learner dictionaries frequently draw on corpus evidence for examples, frequency, grammar and collocation. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

93. Data-Driven Learning

Learners can examine concordance lines and infer patterns directly from evidence. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

94. Discovery Learning

Corpus exploration can make learners active investigators of word behaviour rather than passive recipients of rules. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

95. Guided Corpus Learning

Teachers can reduce cognitive load by preselecting examples and questions before open exploration. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

96. Beginner Corpus Use

Beginners can work with small curated concordance sets without needing technical statistics. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

97. Advanced Corpus Use

Advanced learners can investigate register, semantic prosody, collocation and phraseology independently. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

98. Corpus Use with AI

AI can generate candidate phrases, while corpus evidence can verify whether those candidates appear naturally in the intended register. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

99. Corpus Use with Dictionaries

The strongest workflow often combines dictionary definitions with corpus evidence of real distribution. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

100. The Mastery Club Rule for Corpus Linguistics

Use corpus evidence to test language hypotheses, but always interpret counts through context, domain, dispersion, register and the learner’s real goal. For vocabulary learning, the important move is to translate this corpus concept into a language decision. A count, concordance or statistic matters only when it helps answer a clear question about which word to learn, which phrase to trust, which meaning is common, which register fits or which pattern deserves practice.

A disciplined corpus workflow starts with the question before the tool. Define the target item, choose a corpus that matches the intended language domain, run the simplest search that can answer the question, and inspect actual examples before drawing conclusions. Large numbers without context can create false confidence.

The next step is comparison. Compare alternative words, competing collocations, genres, time periods or subcorpora. Relative patterns are often more informative than a single isolated frequency. If one phrase is common in academic prose but rare in conversation, that difference becomes a register lesson rather than merely a count.

Finally return the evidence to vocabulary use. Record the most useful pattern, retrieve it later, and apply it in a new sentence or task. Corpus study earns its place when it improves comprehension, selection, collocation, register or productive fluency rather than becoming data collection for its own sake.

80 Corpus Linguistics Learning Labs

1. Build a frequency list

Build a frequency list begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

2. Compare raw and normalised frequency

Compare raw and normalised frequency begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

3. Compare two subcorpora

Compare two subcorpora begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

4. Check dispersion

Check dispersion begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

5. Check range

Check range begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

6. Run a lemma search

Run a lemma search begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

7. Run an exact-form search

Run an exact-form search begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

8. Run a POS-tagged search

Run a POS-tagged search begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

9. Build a KWIC concordance

Build a KWIC concordance begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

10. Sort left context

Sort left context begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

11. Sort right context

Sort right context begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

12. Identify a collocate

Identify a collocate begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

13. Compare collocation candidates

Compare collocation candidates begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

14. Check an association score

Check an association score begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

15. Inspect rare collocations manually

Inspect rare collocations manually begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

16. Extract 2-grams

Extract 2-grams begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

17. Extract 3-grams

Extract 3-grams begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

18. Extract 4-grams

Extract 4-grams begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

19. Find lexical bundles

Find lexical bundles begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

20. Run keyword analysis

Run keyword analysis begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

21. Choose a reference corpus

Choose a reference corpus begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

22. Inspect positive keywords

Inspect positive keywords begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

23. Inspect negative keywords

Inspect negative keywords begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

24. Compare spoken and written frequency

Compare spoken and written frequency begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

25. Compare academic and conversation data

Compare academic and conversation data begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

26. Compare British and American usage

Compare British and American usage begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

27. Compare historical and current usage

Compare historical and current usage begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

28. Build a specialised mini-corpus

Build a specialised mini-corpus begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

29. Build a subject textbook corpus

Build a subject textbook corpus begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

30. Build an exam-question corpus

Build an exam-question corpus begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

31. Build a professional email corpus

Build a professional email corpus begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

32. Build a learner corpus sample

Build a learner corpus sample begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

33. Tag recurring learner errors

Tag recurring learner errors begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

34. Verify a dictionary example

Verify a dictionary example begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

35. Verify a thesaurus suggestion

Verify a thesaurus suggestion begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

36. Verify an AI-generated phrase

Verify an AI-generated phrase begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

37. Check a phrasal verb

Check a phrasal verb begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

38. Check a preposition pattern

Check a preposition pattern begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

39. Check a register label

Check a register label begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

40. Check semantic prosody

Check semantic prosody begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

41. Check a technical sense

Check a technical sense begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

42. Check a polysemous word

Check a polysemous word begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

43. Check a near-synonym

Check a near-synonym begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

44. Check a word family

Check a word family begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

45. Check a derived form

Check a derived form begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

46. Check a collocation by genre

Check a collocation by genre begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

47. Check an academic bundle

Check an academic bundle begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

48. Check a spoken discourse marker

Check a spoken discourse marker begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

49. Check a formal phrase

Check a formal phrase begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

50. Check a plain-language alternative

Check a plain-language alternative begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

51. Create a corpus vocabulary notebook

Create a corpus vocabulary notebook begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

52. Create a frequency-plus-dispersion priority list

Create a frequency-plus-dispersion priority list begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

53. Create a collocation card

Create a collocation card begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

54. Create a concordance worksheet

Create a concordance worksheet begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

55. Create a learner discovery task

Create a learner discovery task begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

56. Create a teacher-guided task

Create a teacher-guided task begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

57. Create a writing revision task

Create a writing revision task begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

58. Create a speaking phrase bank

Create a speaking phrase bank begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

59. Create a reading vocabulary map

Create a reading vocabulary map begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

60. Create a listening vocabulary map

Create a listening vocabulary map begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

61. Create a professional glossary

Create a professional glossary begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

62. Create an academic phrase bank

Create an academic phrase bank begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

63. Create a travel phrase bank

Create a travel phrase bank begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

64. Create a science collocation bank

Create a science collocation bank begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

65. Create a math command corpus

Create a math command corpus begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

66. Create a humanities keyword map

Create a humanities keyword map begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

67. Create a corpus-based quiz

Create a corpus-based quiz begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

68. Create a delayed retrieval task

Create a delayed retrieval task begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

69. Create a transfer task

Create a transfer task begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

70. Create a corpus-versus-intuition debate

Create a corpus-versus-intuition debate begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

71. Audit corpus bias

Audit corpus bias begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

72. Audit genre balance

Audit genre balance begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

73. Audit date coverage

Audit date coverage begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

74. Audit regional coverage

Audit regional coverage begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

75. Audit speaker coverage

Audit speaker coverage begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

76. Audit tokenisation

Audit tokenisation begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

77. Audit lemma grouping

Audit lemma grouping begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

78. Audit search query assumptions

Audit search query assumptions begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

79. Audit statistical interpretation

Audit statistical interpretation begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

80. Final corpus evidence report

Final corpus evidence report begins with one explicit vocabulary question. Write the hypothesis before searching so the learner can see whether the evidence confirms, complicates or rejects the original intuition. Choose the corpus by domain and register rather than by size alone.

Run the smallest useful search, then inspect examples. If the task produces a number, ask what was counted: token, lemma, phrase, document range, subcorpus or association score. Corpus literacy means knowing what the output represents and what it does not represent.

Finish with a language decision. Select a phrase, revise a sentence, prioritise a word, change a register label or design a retrieval task. A corpus exercise is complete when evidence changes language understanding or use.

Corpus Linguistics and Vocabulary FAQ

What is corpus linguistics?

Corpus linguistics studies language through systematically collected bodies of written or spoken data.

What is a corpus?

A principled collection of language data assembled for analysis.

What is a vocabulary corpus?

A corpus used to study lexical frequency, meaning, collocation, phraseology or vocabulary distribution.

What is a concordance?

A display of repeated occurrences of a search item with surrounding context.

What does KWIC mean?

Key Word in Context, a concordance format that aligns the search item centrally.

What is a frequency list?

A ranking of items by how often they occur in a corpus.

What is normalised frequency?

A frequency adjusted to a common corpus size so datasets can be compared.

What is dispersion?

A measure of how widely an item is distributed across texts or corpus sections.

Why does dispersion matter?

An item repeated many times in one document may be less generally useful than an item spread across many documents.

What is a collocate?

A word that occurs near a target with meaningful or statistically notable regularity.

What is collocation analysis?

The study of recurring word partnerships using co-occurrence evidence and often association statistics.

What is an n-gram?

A sequence of n tokens extracted from running text.

What is a lexical bundle?

A frequent recurring multiword sequence characteristic of a corpus or register.

What is a keyword in corpus linguistics?

A word unusually frequent or infrequent in a target corpus relative to a reference corpus.

Is corpus keyword analysis the same as SEO keywords?

No. Corpus keyness is a statistical comparison between corpora, while SEO keywords concern search queries and discoverability.

What is a reference corpus?

The comparison corpus used to establish what is ordinary relative to a target corpus.

What is a spoken corpus?

A corpus built from transcribed speech such as conversations, lectures or interviews.

What is a learner corpus?

A corpus containing language produced by learners.

What is a specialised corpus?

A corpus focused on one field, genre, profession or discourse community.

What is a parallel corpus?

A corpus aligning texts and their translations across languages.

What is corpus-based vocabulary learning?

Using corpus evidence to choose, understand, compare and practise vocabulary.

How do corpora help vocabulary learning?

They reveal frequency, collocation, phraseology, register, sense patterns and authentic examples.

How do corpora help writing?

Writers can verify natural phrases, collocations and genre-specific usage.

How do corpora help speaking?

Spoken corpora reveal conversational vocabulary, discourse markers and recurring multiword units.

How do corpora help listening?

They help identify frequent spoken items and phrase patterns learners are likely to encounter.

How do corpora help reading?

They support prioritisation of frequent and domain-relevant vocabulary.

Do high-frequency words always deserve priority?

Not always. Learner goals, domain, dispersion and transfer value also matter.

Can a rare word be important?

Yes. A term can be rare generally but essential inside a specialist domain.

Is a bigger corpus always better?

No. Relevance, balance, metadata and design can matter more than sheer size.

Can I use Google search counts as corpus evidence?

Search engines are useful discovery tools but their counts and ranking systems are not transparent enough to function as a well-controlled corpus by default.

Can corpora tell me what is correct?

They show documented usage. Grammaticality, institutional standards and genre conventions may require additional evidence.

Can corpus frequency prove that one phrase is better?

Frequency is one signal. Meaning, register, dispersion and context must also be considered.

What is semantic prosody?

A recurring evaluative tendency that emerges from the contexts and collocates around a word.

What is colligation?

Association between lexical items and grammatical patterns.

What is part-of-speech tagging?

Automatic or manual annotation identifying grammatical categories such as noun, verb or adjective.

What is lemmatization?

Grouping inflectional forms under a base dictionary-like lemma.

What is tokenisation?

Dividing running language into units for computational analysis.

What is data-driven learning?

A teaching approach in which learners inspect language data and infer patterns from evidence.

Should beginners use corpora?

Yes, if tasks and examples are curated so tool complexity does not overwhelm the vocabulary goal.

How should advanced learners use corpora?

They can investigate collocation, register, phraseology, semantic prosody, domain vocabulary and writing choices.

Can AI replace corpus evidence?

AI can propose language, but corpus evidence remains useful for verifying documented frequency, distribution and genre fit.

Can dictionaries replace corpora?

No. Dictionaries curate meanings and usage; corpora show distributions across many examples. They complement each other.

What are good corpus questions for students?

Which phrase is more common? Which genre uses this word? What nouns follow this adjective? Which verb commonly occurs with this noun?

How should I record corpus findings?

Save the target word, question, corpus, frequency or pattern, several examples, interpretation and one production sentence.

What is the biggest corpus mistake?

Treating a number as self-explanatory without checking corpus design, sense, context or register.

Where should I continue?

Use the Mastery Club Vocabulary apex, Word Frequency, Lexical Profiling, Collocations, Register, Semantic Relations and Lexical Access.