1. 1 Word senses: a computational response Adam Kilgarriff Auckland 2012Kilgarriff: Word senses: a computational response

2. Auckland 2012 Kilgarriff: Word senses: a computational response2 My PhD (in 5 slides)  What is a word sense

3. Auckland 2012 Kilgarriff: Word senses: a computational response3 The lexicographers  They create them  Methods Introspection Other dictionaries Corpus  Atkins, Hanks, Krishnamurthy

4. Auckland 2012 Kilgarriff: Word senses: a computational response4 What is a word sense (1)  SFIP Sufficiently frequent insufficiently predictable  (a glass of) whisky  x (a glass of) tequila

5. Auckland 2012 Kilgarriff: Word senses: a computational response5 What is a word sense (2) homonymy analogy polysemy rules collocation

6. Auckland 2012 Kilgarriff: Word senses: a computational response6 What is a word sense (3)  A cluster Of instances of use  Operationalised as: corpus lines Clustered by lexicographers

7. Auckland 2012 Kilgarriff: Word senses: a computational response7 What is a word sense (3)

8. Auckland 2012 Kilgarriff: Word senses: a computational response8 What is a word sense (3)

9. Auckland 2012 Kilgarriff: Word senses: a computational response9 What is a word sense (3)

10. Auckland 2012 Kilgarriff: Word senses: a computational response10 What is a word sense (3)

11. Auckland 2012 Kilgarriff: Word senses: a computational response11 What is a word sense (3)  A cluster Of instances of use  Operationalised as: corpus lines Clustered by lexicographers  Makes sense of Overlapping senses Different dictionaries, different senses Lumping and splitting

12. Auckland 2012 Kilgarriff: Word senses: a computational response12 I don’t believe in word senses  Believe in: resurrection ghost witch vampire god miracle fairy  Philosophy: Ontological commitment (same meaning different register)  “good entities to build belief systems on”

13. Auckland 2012 Kilgarriff: Word senses: a computational response13 A word sense is a cluster of corpus lines  But I’m an NLP person  Automatic clustering?  Inspiration: Hindle 1991, Schütze 1993, Grefenstette 1993, Lin 1999 You can get semantic sense from corpora+stats

14. Auckland 2012 Kilgarriff: Word senses: a computational response14 First attempt  Longman 1994  Abject failure No grammar Corpus too small and noisy Naïve clustering Useless programmer

15. Auckland 2012 Kilgarriff: Word senses: a computational response15 Collocations  Easy Most words don’t go with most other words  Then build on what we can do well  metaphor, analogy, homonymy, rules all much harder

16. Auckland 2012 Kilgarriff: Word senses: a computational response16 Clustering  Word sketch Collocates organised by grammar  Dictionary Collocates (and other things) organised by meaning  How to re-organise

17. Auckland 2012 Kilgarriff: Word senses: a computational response17 Observation:  corpus: arbitrary sample  dictionary ( =lexicon) : systematic account Children  encounter arbitrary samples  develop systematic account

18. Auckland 2012 Kilgarriff: Word senses: a computational response18 Corpus  provisional, dispensable  used to develop lexicon

19. Auckland 2012 Kilgarriff: Word senses: a computational response19 Levels of abstraction  Direct linkage:  Fragile Updates (to C or D) break links  Dictionary: abstract  Corpus: raw  Intermediate level needed CorpusDictionary ===   ===

20. Auckland 2012 Kilgarriff: Word senses: a computational response20  How most automatic word sense disambiguation (WSD) works Analyse dictionary to give set of collocates Match to collocates in a corpus  Dispensable corpus CorpusDictionary ===   === ===   === Collocates

21. Auckland 2012 Kilgarriff: Word senses: a computational response21 Not just collocates  triples  parse the corpus  some “unary relations” I hear him singing  domain-based clues Collocates, Constructions, Domains = CoCoDo

22. Auckland 2012 Kilgarriff: Word senses: a computational response22  Automatically extract CoCoDos from corpus  How linked to senses? Automatic (WSD techniques) ‏  Manual “dictionary-free”: ideal for new dictionaries Labour costs  Mixed WSD with manual confirmation/correction CorpusDictionary ===   === ===   === CoCoDo CoCoDo Linking CoCoDo’s to senses

23. Auckland 2012 Kilgarriff: Word senses: a computational response23 Semi-automatic dictionary drafting (SADD) ‏  CoCoDo database  Automatic clustering  Lexicographer input  More clustering  Dictionary with corpus inside

24. Auckland 2012 Kilgarriff: Word senses: a computational response24  Automatic clustering of collocates Propose senses  Iterate: Lexicographer input  Confirm/reject/edit sense inventory  Assigns collocates / corpus lines to senses WSD  Uses seeds to build full WSD for word  Find more collocates for each sense  XML dictionary entry Load into dictionary-editing tool

25. Auckland 2012 Kilgarriff: Word senses: a computational response25 Fits with Atkins method for bilingual lexicography  Analyse source language From corpus List all expressions that might possibly have a non-predictable translation  Very fine grained  Lots of collocations target-language-neutral; re-usable  Translate  Edit to finalise dictionary