Corpus linguistics

Short description: Branch of linguistics that studies language through examples contained in real texts

Corpus linguistics is the study of a language as that language is expressed in its text corpus (plural corpora), its body of "real world" text. Corpus linguistics proposes that a reliable analysis of a language is more feasible with corpora collected in the field—the natural context ("realia") of that language—with minimal experimental interference. The large collections of text allow linguistics to run quantitative analyses on linguistic concepts, otherwise harder to quantify.[1]

The text-corpus method uses the body of texts written in any natural language to derive the set of abstract rules which govern that language. Those results can be used to explore the relationships between that subject language and other languages which have undergone a similar analysis. The first such corpora were manually derived from source texts, but now that work is automated.

Corpora have not only been used for linguistics research, they have also been used to compile dictionaries (starting with The American Heritage Dictionary of the English Language in 1969) and grammar guides, such as A Comprehensive Grammar of the English Language, published in 1985.

Experts in the field have differing views about the annotation of a corpus. These views range from John McHardy Sinclair, who advocates minimal annotation so texts speak for themselves,[2] to the Survey of English Usage team (University College, London), who advocate annotation as allowing greater linguistic understanding through rigorous recording.[3]

## Contents

* 1 History
* 1.1 English corpora
* 1.2 Multilingual Corpora
* 1.3 Ancient languages corpora
* 1.4 Corpora from specific fields
* 2 Methods
* 3 See also
* 4 Notes and references
* 5 Further reading
* 5.1 Books
* 5.2 Book series
* 5.3 Journals
* 6 External links

## History

Part of a series on

Linguistics

* Outline
* History
* Index

Subfields

* Acquisition
* Anthropological
* Applied
* Computational
* Discourse analysis
* Forensic
* Historical
* Lexicography
* Morphology
* Morphophonology
* Neurolinguistics
* Philosophy of language
* Phonetics
* Phonology
* Pragmatics
* Psycholinguistics
* Semantics
* Sociolinguistics
* Syntax

Grammatical theories

* Cognitive
* Model-theoretic
* Constituency
* Dependency
* Functional
* Generative
* Stochastic

Topics

* Conservative / innovative forms
* Descriptivism
* Etymology
* Internet linguistics
* LGBT linguistics
* Linguistic anthropology
* Linguistic philosophy
* Origin of language
* Origin of speech
* Orthography
* Prescriptivism
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Some of the earliest efforts at grammatical description were based at least in part on corpora of particular religious or cultural significance. For example, Prātiśākhya literature described the sound patterns of Sanskrit as found in the Vedas, and Pāṇini's grammar of classical Sanskrit was based at least in part on analysis of that same corpus. Similarly, the early Arabic grammarians paid particular attention to the language of the Quran. In the Western European tradition, scholars prepared concordances to allow detailed study of the language of the Bible and other canonical texts.

### English corpora

A landmark in modern corpus linguistics was the publication of Computational Analysis of Present-Day American English in 1967. Written by Henry Kučera and W. Nelson Francis, the work was based on an analysis of the Brown Corpus, which was a contemporary compilation of about a million American English words, carefully selected from a wide variety of sources.[4] Brown's corpus was the first computerized corpus designed for linguistic research.[5] Kučera and Francis subjected the Brown Corpus to a variety of computational analyses and then combined elements of linguistics, language teaching, psychology, statistics, and sociology to create a rich and variegated opus. A further key publication was Randolph Quirk's "Towards a description of English Usage" in 1960[6] in which he introduced the Survey of English Usage. Quirk's corpus was the first modern corpus to be built with the purpose of representing the whole language.[7]

Shortly thereafter, Boston publisher Houghton-Mifflin approached Kučera to supply a million-word, three-line citation base for its new American Heritage Dictionary, the first dictionary compiled using corpus linguistics. The AHD took the innovative step of combining prescriptive elements (how language should be used) with descriptive information (how it actually is used).

Other publishers followed suit. The British publisher Collins' COBUILD monolingual learner's dictionary, designed for users learning English as a foreign language, was compiled using the Bank of English. The Survey of English Usage Corpus was used in the development of one of the most important Corpus-based Grammars, which was written by Quirk et al. and published in 1985 as A Comprehensive Grammar of the English Language.[8]

The Brown Corpus has also spawned a number of similarly structured corpora: the LOB Corpus (1960s British English), Kolhapur (Indian English), Wellington (New Zealand English), Australian Corpus of English (Australian English), the Frown Corpus (early 1990s American English), and the FLOB Corpus (1990s British English). Other corpora represent many languages, varieties and modes, and include the International Corpus of English, and the British National Corpus, a 100 million word collection of a range of spoken and written texts, created in the 1990s by a consortium of publishers, universities (Oxford and Lancaster) and the British Library. For contemporary American English, work has stalled on the American National Corpus, but the 400+ million word Corpus of Contemporary American English (1990–present) is now available through a web interface.

The first computerized corpus of transcribed spoken language was constructed in 1971 by the Montreal French Project,[9] containing one million words, which inspired Shana Poplack's much larger corpus of spoken French in the Ottawa-Hull area.[10]

### Multilingual Corpora

In the 1990s, many of the notable early successes on statistical methods in natural-language programming (NLP) occurred in the field of machine translation, due especially to work at IBM Research. These systems were able to take advantage of existing multilingual textual corpora that had been produced by the Parliament of Canada and the European Union as a result of laws calling for the translation of all governmental proceedings into all official languages of the corresponding systems of government.

There are corpora in non-European languages as well. For example, the National Institute for Japanese Language and Linguistics in Japan has built a number of corpora of spoken and written Japanese. Sign language corpora have also been created using video data.[11]

### Ancient languages corpora

Besides these corpora of living languages, computerized corpora have also been made of collections of texts in ancient languages. An example is the Andersen-Forbes database of the Hebrew Bible, developed since the 1970s, in which every clause is parsed using graphs representing up to seven levels of syntax, and every segment tagged with seven fields of information.[12][13] The Quranic Arabic Corpus is an annotated corpus for the Classical Arabic language of the Quran. This is a recent project with multiple layers of annotation including morphological segmentation, part-of-speech tagging, and syntactic analysis using dependency grammar.[14] The Digital Corpus of Sanskrit (DCS) is a "Sandhi-split corpus of Sanskrit texts with full morphological and lexical analysis... designed for text-historical research in Sanskrit linguistics and philology."[15]

### Corpora from specific fields

Besides pure linguistic inquiry, researchers had begun to apply corpus linguistics to other academic and professional fields, such as the emerging sub-discipline of Law and Corpus Linguistics, which seeks to understand legal texts using corpus data and tools. The DBLP Discovery Dataset concentrates on computer science, containing relevant computer science publications with sentient metadata such as author affiliations, citations, or study fields.[16] A more focused dataset was introduced by NLP Scholar, a combination of papers of the ACL Anthology and Google Scholar metadata.[17] Corpora can also aid in translation efforts[18] or in teaching foreign languages.[19]

## Methods

Corpus linguistics has generated a number of research methods, which attempt to trace a path from data to theory. Wallis and Nelson (2001)[20] first introduced what they called the 3A perspective: Annotation, Abstraction and Analysis.

* Annotation consists of the application of a scheme to texts. Annotations may include structural markup, part-of-speech tagging, parsing, and numerous other representations.
* Abstraction consists of the translation (mapping) of terms in the scheme to terms in a theoretically motivated model or dataset. Abstraction typically includes linguist-directed search but may include e.g., rule-learning for parsers.
* Analysis consists of statistically probing, manipulating and generalising from the dataset. Analysis might include statistical evaluations, optimisation of rule-bases or knowledge discovery methods.

Most lexical corpora today are part-of-speech-tagged (POS-tagged). However even corpus linguists who work with 'unannotated plain text' inevitably apply some method to isolate salient terms. In such situations annotation and abstraction are combined in a lexical search.

The advantage of publishing an annotated corpus is that other users can then perform experiments on the corpus (through corpus managers). Linguists with other interests and differing perspectives than the originators' can exploit this work. By sharing data, corpus linguists are able to treat the corpus as a locus of linguistic debate and further study.[21]

## See also

* A Linguistic Atlas of Early Middle English
* Collocation
* Collostructional analysis
* Concordance (KWIC)
* Keyword (linguistics)
* Linguistic Data Consortium
* List of text corpora
* Machine translation
* Natural Language Toolkit
* Pattern grammar
* Search engines: they access the "web corpus"
* Semantic prosody
* Speech corpus
* Text corpus
* Translation memory
* Treebank
* Word list

## Notes and references

1. ↑ Hunston, S. (2006-01-01), Brown, Keith, ed., "Corpus Linguistics", Encyclopedia of Language & Linguistics (Second Edition) (Oxford: Elsevier): pp. 234–248, doi:10.1016/b0-08-044854-2/00944-5, ISBN 978-0-08-044854-1, https://www.sciencedirect.com/science/article/pii/B0080448542009445, retrieved 2023-10-31
2. ↑ Sinclair, J. 'The automatic analysis of corpora', in Svartvik, J. (ed.) Directions in Corpus Linguistics (Proceedings of Nobel Symposium 82). Berlin: Mouton de Gruyter. 1992.
3. ↑ Wallis, S. 'Annotation, Retrieval and Experimentation', in Meurman-Solin, A. & Nurmi, A.A. (ed.) Annotating Variation and Change. Helsinki: Varieng, [University of Helsinki]. 2007. e-Published
4. ↑ Francis, W. Nelson; Kučera, Henry (1 June 1967). Computational Analysis of Present-Day American English. Providence: Brown University Press. ISBN 978-0870571053.
5. ↑ Kennedy, G. (2001-01-01), Smelser, Neil J.; Baltes, Paul B., eds., "Corpus Linguistics", International Encyclopedia of the Social & Behavioral Sciences (Oxford: Pergamon): pp. 2816–2820, ISBN 978-0-08-043076-8, https://www.sciencedirect.com/science/article/pii/B0080430767030564, retrieved 2023-10-31
6. ↑ Quirk, Randolph (November 1960). "Towards a description of English Usage". Transactions of the Philological Society 59 (1): 40–61. doi:10.1111/j.1467-968X.1960.tb00308.x.
7. ↑ Kennedy, G. (2001-01-01), Smelser, Neil J.; Baltes, Paul B., eds., "Corpus Linguistics", International Encyclopedia of the Social & Behavioral Sciences (Oxford: Pergamon): pp. 2816–2820, doi:10.1016/b0-08-043076-7/03056-4, ISBN 978-0-08-043076-8, https://www.sciencedirect.com/science/article/pii/B0080430767030564, retrieved 2023-10-31
8. ↑ Quirk, Randolph; Greenbaum, Sidney; Leech, Geoffrey; Svartvik, Jan (1985). A Comprehensive Grammar of the English Language. London: Longman. ISBN 978-0582517349.
9. ↑ Sankoff, David; Sankoff, Gillian (1973). Darnell, R.. ed. "Sample survey methods and computer-assisted analysis in the study of grammatical variation". Canadian Languages in Their Social Context (Edmonton: Linguistic Research Incorporated): 7–63.
10. ↑ Poplack, Shana (1989). "The care and handling of a mega-corpus". Language Change and Variation. Current Issues in Linguistic Theory (Amsterdam: Benjamins) 52: 411–451. doi:10.1075/cilt.52.25pop. ISBN 978-90-272-3546-6.
11. ↑ "National Center for Sign Language and Gesture Resources at B.U.". https://www.bu.edu/asllrp/cslgr/.
12. ↑ Andersen, Francis I.; Forbes, A. Dean (2003), "Hebrew Grammar Visualized: I. Syntax", Ancient Near Eastern Studies 40: 43–61 [45]
13. ↑ Eyland, E. Ann (1987), "Revelations from Word Counts", in Newing, Edward G.; Conrad, Edgar W., Perspectives on Language and Text: Essays and Poems in Honor of Francis I. Andersen's Sixtieth Birthday, July 28, 1985, Winona Lake, IN: Eisenbrauns, p. 51, ISBN 0-931464-26-9
14. ↑ Dukes, K., Atwell, E. and Habash, N. 'Supervised Collaboration for Syntactic Annotation of Quranic Arabic'. Language Resources and Evaluation Journal. 2011.
15. ↑ "Digital Corpus of Sanskrit (DCS)". http://www.sanskrit-linguistics.org/dcs/#:~:text=The Digital Corpus of Sanskrit,in Sanskrit linguistics and philology..
16. ↑ Wahle, Jan Philip; Ruas, Terry; Mohammad, Saif; Gipp, Bela (2022). "D3: A Massive Dataset of Scholarly Metadata for Analyzing the State of Computer Science Research". Proceedings of the Thirteenth Language Resources and Evaluation Conference (Marseille, France: European Language Resources Association): 2642–2651. https://aclanthology.org/2022.lrec-1.283.
17. ↑ Mohammad, Saif M. (2020). "NLP Scholar: A Dataset for Examining the State of NLP Research" (in English). Proceedings of the Twelfth Language Resources and Evaluation Conference (Marseille, France: European Language Resources Association): 868–877. ISBN 979-10-95546-34-4. https://aclanthology.org/2020.lrec-1.109.
18. ↑ Bernardini, S. (2006-01-01), Brown, Keith, ed., "Machine Readable Corpora", Encyclopedia of Language & Linguistics (Second Edition) (Oxford: Elsevier): pp. 358–375, doi:10.1016/b0-08-044854-2/00476-4, ISBN 978-0-08-044854-1, https://www.sciencedirect.com/science/article/pii/B0080448542004764, retrieved 2023-10-31
19. ↑ Mainz, Johannes Gutenberg-Universität. "Corpus Linguistics | ENGLISH LINGUISTICS" (in de-DE). https://www.english-linguistics.uni-mainz.de/corpus-linguistics/.
20. ↑ Wallis, S. and Nelson G. Knowledge discovery in grammatically analysed corpora. Data Mining and Knowledge Discovery, 5: 307–340. 2001.
21. ↑ Baker, Paul, ed (2016). Triangulating Methodological Approaches in Corpus-Linguistic Research. New York: Routledge.

## Further reading

### Books

* Biber, D., Conrad, S., Reppen R. Corpus Linguistics, Investigating Language Structure and Use, Cambridge: Cambridge UP, 1998. ISBN:0-521-49957-7
* McCarthy, D., and Sampson G. Corpus Linguistics: Readings in a Widening Discipline, Continuum, 2005. ISBN:0-8264-8803-X
* Facchinetti, R. Theoretical Description and Practical Applications of Linguistic Corpora. Verona: QuiEdit, 2007 ISBN:978-88-89480-37-3
* Facchinetti, R. (ed.) Corpus Linguistics 25 Years on. New York/Amsterdam: Rodopi, 2007 ISBN:978-90-420-2195-2
* Facchinetti, R. and Rissanen M. (eds.) Corpus-based Studies of Diachronic English. Bern: Peter Lang, 2006 ISBN:3-03910-851-4
* Lenders, W. Computational lexicography and corpus linguistics until ca. 1970/1980, in: Gouws, R. H., Heid, U., Schweickard, W., Wiegand, H. E. (eds.) Dictionaries – An International Encyclopedia of Lexicography. Supplementary Volume: Recent Developments with Focus on Electronic and Computational Lexicography. Berlin: De Gruyter Mouton, 2013 ISBN:978-3112146651
* Fuß, Eric et al. (Eds.): Grammar and Corpora 2016, Heidelberg: Heidelberg University Publishing, 2018. doi: 10.17885/heiup.361.509 (digital open access).
* Stefanowitsch A. 2020. Corpus linguistics: A guide to the methodology. Berlin: Language Science Press. ISBN:978-3-96110-225-9, doi:10.5281/zenodo.3735822 Open Access https://langsci-press.org/catalog/book/148.

### Book series

Book series in this field include:

* Language and Computers (Brill)
* Studies in Corpus Linguistics (John Benjamins)
* English Corpus Linguistics (Peter Lang)
* Corpus and Discourse (Bloomsbury)

### Journals

There are several international peer-reviewed journals dedicated to corpus linguistics, for example:

* Corpora
* Corpus Linguistics and Linguistic Theory
* ICAME Journal
* International Journal of Corpus Linguistics
* Language Resources and Evaluation Journal, supported by the European Language Resources Association
* Research in Corpus Linguistics, supported by the Spanish Association for Corpus Linguistics (AELINCO)

## External links

* Bookmarks for Corpus-based Linguists – very comprehensive site with categorized and annotated links to language corpora, software, references, etc.
* Corpora discussion list
* Freely-available, web-based corpora (100 million – 400 million words each): American (COCA, COHA), British (BNC), Time, Spanish, Portuguese
* Manuel Barbera's overview site
* AskOxford.com the composition and use of the Oxford Corpus
* DMCBC.com
* Datum Multilanguage Corpora Based on chinese free sample download
* Corpus4u Community a Chinese online forum for corpus linguistics
* McEnery and Wilson's Corpus Linguistics Page
* Corpus Linguistics with R mailing list
* Research and Development Unit for English Studies
* Survey of English Usage
* The Centre for Corpus Linguistics at Birmingham University
* Tools for Corpus Linguistics (annotated list)
* Gateway to Corpus Linguistics on the Internet: an annotated guide to corpus resources on the web
* Biomedical corpora
* Linguistic Data Consortium, a major distributor of corpora
* Penn Parsed Corpora of Historical English
* Corsis: (formerly Tenka Text) an open-source (GPLed) corpus analysis tool written in C#
* ICECUP and Fuzzy Tree Fragments
* Discussion group text mining
* A corpus linguistics related conference MAG 2017: You can find some information and events related to Metadiscourse Across Genres by visiting MAG 2017 website.
* Corpus of Political Speeches, Free access to political speeches by American and Chinese politicians, developed by Hong Kong Baptist University Library
* LightTag -Text Annotation Tool, A text annotation tool for machine learning corpus focused on team management
* LIVAC Synchronous Corpus

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Natural language processing

General terms|

* AI-complete
* Bag-of-words
* n-gram
* Bigram
* Trigram
* Computational linguistics
* Natural-language understanding
* Stop words
* Text processing

Text analysis|

* Collocation extraction
* Concept mining
* Coreference resolution
* Deep linguistic processing
* Distant reading
* Information extraction
* Named-entity recognition
* Ontology learning
* Parsing
* Part-of-speech tagging
* Semantic role labeling
* Semantic similarity
* Sentiment analysis
* Terminology extraction
* Text mining
* Textual entailment
* Truecasing
* Word-sense disambiguation
* Word-sense induction

| Text segmentation|

* Compound-term processing
* Lemmatisation
* Lexical analysis
* Text chunking
* Stemming
* Sentence segmentation
* Word segmentation

|

Automatic summarization|

* Multi-document summarization
* Sentence extraction
* Text simplification

Machine translation|

* Computer-assisted
* Example-based
* Rule-based
* Statistical
* Transfer-based
* Neural

Distributional semantics models|

* BERT
* Document-term matrix
* Explicit semantic analysis
* fastText
* GloVe
* Latent semantic analysis
* Word embedding
* Word2vec

Language resources,
datasets and corpora|

| Types and
standards|

* Corpus linguistics
* Lexical resource
* Linguistic Linked Open Data
* Machine-readable dictionary
* Parallel text
* PropBank
* Semantic network
* Simple Knowledge Organization System
* Speech corpus
* Text corpus
* Thesaurus (information retrieval)
* Treebank
* Universal Dependencies

|

Data|

* BabelNet
* Bank of English
* DBpedia
* FrameNet
* Google Ngram Viewer
* UBY
* WordNet

Automatic identification
and data capture|

* Speech recognition
* Speech segmentation
* Speech synthesis
* Natural language generation
* Optical character recognition

Topic model|

* Document classification
* Latent Dirichlet allocation
* Pachinko allocation

Computer-assisted
reviewing|

* Automated essay scoring
* Concordancer
* Grammar checker
* Predictive text
* Spell checker
* Syntax guessing

Natural language
user interface|

* Chatbot
* Interactive fiction
* Question answering
* Virtual assistant
* Voice user interface

Other software|

* Natural Language Toolkit
* spaCy

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