Corpus linguistics is the study of language as expressed in corpora (samples) of “real world” text. Corpus linguistics proposes that reliable language analysis is more feasible with corpora collected in the field in its natural context (“realia”), and with minimal experimental-interference. The field of corpus linguistics features divergent views about the value of corpus annotation. These views range from John McHardy Sinclair, who advocates minimal annotation so texts speak for themselves,to the Survey of English Usage team (University College, London), who advocate annotation as allowing greater linguistic understanding through rigorous recording. The text-corpus method is a digestive approach that derives a set of abstract rules that govern a natural language from texts in that language, and explores how that language relates to other languages. Originally derived manually, corpora now are automatically derived from source texts. In addition to linguistics research, assembled corpora have 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.
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.
A landmark in modern corpus linguistics was the publication by Henry Kučera and W. Nelson Francis of Computational Analysis of Present-Day American English in 1967, a work based on the analysis of the Brown Corpus, a carefully compiled selection of current American English, totalling about a million words drawn from a wide variety of sources. Kučera and Francis subjected it to a variety of computational analyses, from which they compiled a rich and variegated opus, combining elements of linguistics, language teaching, psychology, statistics, and sociology. A further key publication was Randolph Quirk’s ‘Towards a description of English Usage’ (1960) in which he introduced The Survey of English Usage.
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, the Comprehensive Grammar of English (Quirk et al. 1985).
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, containing one million words, which inspired Shana Poplack’s much larger corpus of spoken French in the Ottawa-Hull area.
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. 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.
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.
Corpus linguistics has generated a number of research methods, which attempt to trace a path from data to theory. Wallis and Nelson (2001) 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.