Corpus Mark-up

1. Corpus Mark-up UoL Summer Institute in Corpus Linguistics Matthew Brook O’Donnell

2. Aims • Introduce the concepts of corpus mark-up and annotation • Consider why we would want to add extra non-textual information to corpus texts • Use a pos-tagger and tagged text

3. What is Corpus Annotation? • ‘the practice of adding interpretative linguistic information to a corpus’ (Leech 2005) • interpretative • linguistic • results in -> value-added corpus

4. Terminology • Corpus Markup • processing/formatting information • metadata/text classifications • structural representation • Tagging • (usually) inline addition of category to word(s) • Parsing • higher-level, multiword units (constituents) • chunking/shallow vs. full syntactical parsing • needn’t just be syntactical analysis • XML • eXtensible Markup Language

5. Why Annotate? • Manual examination of corpus • Automatic analysis of corpus • Reusability of annotations • Multi-functionality • Objective record of analysis • Annotation process is corpus analysis Leech 2005 McEnery 2003 O’Donnell 1999

6. Types of Corpus Annotation • Part-of-speech (POS) • Lemmatization • Syntactical (parsing) • Semantic (domain classifications) • Coreference (Discourse) • Pragmatic (Speech acts – dialogue) • Stylistic • Research specific (ad hoc)

7. POS Tagging: Claws C5 Corpus_NN1 annotation_NN1 is_VBZ the_AT0 practice_NN1 of_PRF adding_VVG interpretative_AJ0 linguistic_AJ0 information_NN1 to_PRP a_AT0 corpus_NN1 ._. NN1 singular noun AJ0 adjective (unmarked) VBZ -s form of the verb "BE“ PRF the preposition OF VVG -ing form of lexical verb AT0 article

8. POS Tagging: Claws C7 Corpus_NN1 annotation_NN1 is_VBZ the_AT practice_NN1 of_IO adding_VVG interpretative_JJ linguistic_JJ information_NN1 to_II a_AT1 corpus_NN1 ._. http://www.comp.lancs.ac.uk/ucrel/claws/trial.html

9. POS Tagging: POSTagger Corpus/NN annotation/NN is/VBZ the/DT practice/NN of/IN adding/VBG interpretative/JJ linguistic/JJ information/NN to/TO a/DT corpus/NN ./.

10. Parsing: Chunking [NP (NN Corpus) (NN annotation) ] (VBZ is) [NP (DT the) (NN practice) ] (IN of) (VBG adding) [NP (JJ interpretative) (JJ linguistic) (NN information) ] [PP (TO to) [NP (DT a) (NN corpus) ]

11. Parsing (S (NP Corpus annotation) (VP is (NP (NP the practice) (PP of (S (VP adding (NP interpretative linguistic information) (PP to (NP a corpus)) )) ) ) ) .)

12. Semantic Annotation • Each word given code from thesaurus-style dictionary • Also called Word Sense Tagging • Examples • UCREL Semantic Analysis System [http://www.comp.lancs.ac.uk/ucrel/usas/] • WordNet [http://wordnet.princeton.edu/]

13. Semantic Annotation • The noun move has 5 senses (first 5 from tagged texts) • 1. (377) move -- (the act of deciding to do something; "he didn't make a move to help"; "his first move was to hire a lawyer") • 2. (70) move, relocation -- (the act of changing your residence or place of business; "they say that three moves equal one fire") • 3. (57) motion, movement, move, motility -- (a change of position that does not entail a change of location; "the reflex motion of his eyebrows revealed his surprise"; "movement is a sign of life"; "an impatient move of his hand"; "gastrointestinal motility") • 4. (30) motion, movement, move -- (the act of changing location from one place to another; "police controlled the motion of the crowd"; "the movement of people from the farms to the cities"; "his move put him directly in my path") • 5. (5) move -- ((game) a player's turn to take some action permitted by the rules of the game)

14. Semantic Annotation • The verb move has 16 senses (first 13 from tagged texts) • 1. (130) travel, go, move, locomote -- (change location; move, travel, or proceed; "How fast does your new car go?"; "We travelled from Rome to Naples by bus"; "The policemen went from door to door looking for the suspect"; "The soldiers moved towards the city in an attempt to take it before night fell") • 2. (60) move, displace -- (cause to move, both in a concrete and in an abstract sense; "Move those boxes into the corner, please"; "I'm moving my money to another bank"; "The director moved more responsibilities onto his new assistant") • 3. (52) move -- (move so as to change position, perform a nontranslational motion; "He moved his hand slightly to the right") • 4. (20) move -- (change residence, affiliation, or place of employment; "We moved from Idaho to Nebraska"; "The basketball player moved from one team to another")

15. Tools • XML • Annotation Editors • GATE • WordSmith

16. The ‘Great Annotation Debate’ • Leech et al. ‘annotation = value added’ • Sinclair ‘annotation = perilous activity’ • Scott ‘beware of the POS prison!’

17. Sinclair on the perils of corpus annotation • ‘The interspersing of tags in a language text is a perilous activity, because the text thereby loses integrity…’ ‘Current Issues in Corpus Linguistics’ (Sinclair 2004: 191)

18. Sinclair on the perils of corpus annotation • ‘..one cosy consequence of using tagged text is that the description which produces the tags in the first place is not challenged – it is protected. The corpus data can only be observed through the tags; that is to say, anything the tags are not sensitive to will be missed’ ‘Current Issues in Corpus Linguistics’ (Sinclair 2004: 191)

19. Sinclair on the perils of corpus annotation • ‘In corpus-driven linguistics you do not use pre-tagged text, but you process the raw text directly and then patterns of this uncontaminated text are able to be observed.’ ‘Current Issues in Corpus Linguistics’ (Sinclair 2004: 191)

20. Hunston – annotation as ‘double-edged sword’ • ‘…the categories used to annotate a corpus are typically determined before any corpus analysis is carried out, which in turn tends to limit, not the kind of question that can be asked, but the kind of question that usually is asked.’ (Hunston 2002: 93)

21. Hunston – annotation as ‘double-edged sword’ • ‘Most of the work that is done using annotated corpora uses categories that have been developed in pre-corpus days, such as nominal clauses, anaphoric reference… Phenomena such as frames or semantic prosody… tend to have been identified from plain text corpora and word-based studies.’ (Hunston 2002: 93)

22. Corpus-based approach annotated corpus CORPUS METHODS ANALYSIS categorization DATA plain corpus ANALYSIS generalization • Annotate Corpus • POS • Parsing • Semantic • Reference RESULTS

23. Corpus-driven approach plain corpus CORPUS METHODS DATA ANALYSIS generalization & categorization RESULTS

24. Problem for both CB & CD Approach • Serial/Sequential process • CB analysis before (annotation) and after processing • CD analysis only after processing (so no need for annotation) • Empirical process is cyclic • analysis feeds back into process and around again… and again…

25. So what if…. • Hunston - ‘Most of the work that is done using annotated corpora uses categories that have been developed in pre-corpus days….’ • we annotate categories that have come out of corpus analysis instead of/as well as traditional categories? (Hunston 2002: 93)

26. New uses for corpus annotation • Cyclic investigation process • KWIC/Frequency list/Collocates etc. • Annotate results • Goto 1 • How sould we annotate: • collocates • lexical items • semantic associations/prosodies • Local textual functions

27. References Leech, G 2005 ‘Adding Linguistic Annotation’, in M. Wynne, Developing Linguistic Corpora: a Guide to Good Practice (Oxford: Oxbrow Books), pp. 17-29 [http://ahds.ac.uk/linguistic-corpora/] Hunston, S. 2002 Corpora in Applied Linguistics (Cambridge: Cambridge University Press) McEnery, A 2003 ‘Corpus Linguistics’, in R. Mitov (ed.), The Oxford Handbook of Computational Linguistics (Oxford: Oxford University Press), pp. 448-463

28. References O’Donnell, M.B. ‘The Use of Annotated Corpora for New Testament Discourse Analysis: A Survey of Current Practice and Future Prospects’, in S.E. Porter and J.T. Reed (eds.), Discourse Analysis and the New Testament: Results and Applications (Sheffield: Sheffield Academic Press, 1999), pp. 71-117. Sinclair, J. 2004 Trust the Text: Language, Corpus and Discourse (London: Routledge)