1. LING 388: Language and Computers Sandiway Fong Lecture 23: 11/15

2. Administrivia Reminder –Homework 4, the milestone homework... –due today

3. Last Time the puzzle of language –language is a complex system in terms of shades of meaning, syntax, what is allowed and what is not –language is part of a generative system you can compose constructions and create new sentences people can have sharp judgments about data they have never seen before –Plato’s Problem: poverty of stimulus is there enough data to determine the grammar we have? is part of language pre-wired into us?

4. Last Time example: a mechanism for gap-filling –which report did you file without reading? file(filer[you],[which report]) & read(reader,something) & filer=reader & something = [which report] which report did you file [the report] without [you] reading [the report] *which book did you file the report without reading famous example –(1) colorless green ideas sleep furiously –(2) furiously sleep ideas green colorless –Peirera’s statistical experiment: P(1)/P(2) ≈ 200,000

5. New Topic Semantic Inference and Language computation using –WordNet project led by a psychologist –George Miller (Princeton University) handbuilt network of synonym sets (synsets) with semantic relations connecting them –you’ll need to download software for the upcoming Homework 5 wnconnect: WordNet connect –available for MacOS X, Linux and Windows download from –http://dingo.sbs.arizona.edu/~sandiway/wnconnect/

6. Example

7. Two Problems –linguistically relevant puzzles –outside syntax 1.Semantic Opposition 2.Logical Metonomy

8. Semantic Opposition Event-based Models of Change and Persistence in Language (Pustejovsky, 2000): –John mended the torn dress –John mended the red dress –what kind of knowledge is invoked here? from Artificial Intelligence (AI): –an instance of the frame problem –aka the update problem –computation: what changes in the world and what doesn’t?

9. WordNet for more background and details, see –5 Papers on WordNet from the Princeton team 5papers.pdf

10. WordNet what is it? –synonym set (synset) network for nouns, verbs, adjectives and adverbs –synsets connected by semantic relations (isa, antonymy,...) –139,000 entries (word senses) –10,000 verbs (polysemy 2), 20,000 adjectives (1.5) –originally conceived as a model of human semantic memory

11. WordNet what is it? –synonym set (synset) network for nouns, verbs, adjectives and adverbs –synsets connected by semantic relations (isa, antonymy,...) –139,000 entries (word senses), 10,000 verbs (polysemy 2), 20,000 adjectives (1.5) –originally conceived as a model of human semantic memory

12. WordNet what is it? –synonym set (synset) network for nouns, verbs, adjectives and adverbs –synsets connected by semantic relations (isa, antonymy,...) –139,000 entries (word senses), 10,000 verbs (polysemy 2), 20,000 adjectives (1.5) –originally conceived as a model of human semantic memory

13. WordNet extremely popular resource for language applications –freely available (project cost $3M) –many Wordnets based on the Princeton system have been proposed or built for other languages EuroWordNet (EWN) ItalWordNet Tamil WordNet Estonian WordNet

14. WordNet Applications examples –information retrieval and extraction query term expansion (synonyms etc.) cross-linguistic information retrieval (multilingual WordNet) –concept identification in natural language word sense disambiguation WordNet senses and ontology (isa-hierarchy) –semantic distance computation relatedness of words –document structuring and categorization determine genre of a paper (WordNet verb categories)

15. WordNet Relations RelationDescriptionExample x HYP yx is a hypernym of yx: repair, y: improve x ENT yx entails yx: breathe, y: inhale x SIM yy is similar to x (A)x: achromatic, y: white x CS yy is a cause of xx: anesthetize, y: sleep x VGP yy is similar to x (V)x: behave, y: pretend x ANT yx and y are antonymsx: present, y: absent x SA yx, see also yx: breathe, y: breathe out x PPL yx participle of yx: applied, y: apply x PER yx pertains to yx: abaxial, y: axial

16. Back to Semantic Opposition...

17. Persistence and Change of State Verbs Event-based Models of Change and Persistence in Language (Pustejovsky, 2000): –John mended the torn dress –John mended the red dress Verb Classes: Aspectual Classes (Vendler 1967) –Mary cleaned the dirty tableChange of State –The waiter filled every empty glass –Mary fixed the flat tire –Bill swept the dirty floorActivity –Bill swept the dirty floor cleanAccomplishment –Nero built the gleaming templeCreation –Nero ruined the splendid templeDestruction

18. Event Representation Change of State Verbs: –John mended the torn/red dress –mend: x CAUS y BECOME –John CAUS the torn/red dress BECOME antonym relation between adjective and the end state

19. Using wnconnect Find shortest link between mend and tear in WordNet:

20. Using wnconnect Find shortest link between mend and tear in WordNet: –mend/v is in [repair,mend,fix,bushel,doctor,furbish_up,restore,touch_on] –repair and break/v are antonyms –bust in [break,bust] and bust/v related by verb.contact –tear/v is in the synset [tear,rupture,snap,bust]

21. Using wnconnect two senses of bust: (1) to ruin completely, (2) to separate or cause to separate abruptly

22. Using wnconnect –John CAUS the red dress BECOME mend/n is in [mend,patch] [mend,patch] is an instance of [sewing,stitchery] [sewing,stitchery] is an instance of [needlework,needlecraft] [needlework,needlecraft] is an instance of [creation] [creation] is an instance of [artifact,artefact] [artifact,artefact] is an instance of [object,physical_object] [object,physical_object] is an instance of [entity,physical_thing] [causal_agent,cause,causal_agency] is an instance of [entity,physical_thing] [person,individual,someone,somebody,mortal,human,soul] is an instance of [causal_agent,cause,causal_agency] [disputant,controversialist] is an instance of [person,individual,someone,somebody,mortal,human,soul] [radical] is an instance of [disputant,controversialist] [Bolshevik,Marxist,pinko,red,bolshie] is an instance of [radical] red/n is in the synset [Bolshevik,Marxist,pinko,red,bolshie]

23. Using wnconnect –John CAUS the red dress BECOME

24. Results

25. Thresholding –No upper limit on the length of the shortest chain example –fix–blue: 11 links (no semantic opposition) cf. rescue–drowning: 13 links (semantic opposition)

26. Shortest Path Criterion –Take the shortest chain example –fix–flat: no chain found

27. Shortest Path mend–tear all paths

28. Color it’s not always clear how (or if we should) organize terms in a network –example WordNet organizes color by chromaticity blue–white: no semantic opposition found

29. Color –WordNet organizes color by chromaticity Example: –blue–white: no semantic opposition found both chromatic –John painted the red door blue both achromatic –Mary painted the white tiles grey

30. Two Problems –linguistically relevant puzzles –outside syntax 1.Semantic Opposition 2.Logical Metonomy

31. Logical Metonomy –also can be thought of an example of gap filling –with eventive verbs: begin and enjoy examples –John began the novel(reading/writing) –John began [reading/writing] the novel –X began Y ⇒ X began V-ing Y –The author began the unfinished novel back in 1962(writing) –The author began [writing] the unfinished novel back in 1962

32. Logical Metonomy –also can be thought of an example of gap filling... –Pustejovsky (1995), Lascarides & Copestake (1995) and Verspoor (1997) –eventive verbs: begin and enjoy examples –John began the novel(reading/writing) –The author began the unfinished novel back in 1962(writing) one idea about the organization of the lexicon (GL) –novel: qualia structure: telic role: read(purpose/function) agentive role: writing(creation) constitutive role: narrative (parts) formal role: book, disk(physical properties)

33. Logical Metonomy examples –John began the novel(reading/writing) –The author began the unfinished novel back in 1962(writing) More Examples: (enjoy) –Mary enjoyed [reading] the novel(reading) –!!The visitor enjoyed [verb] the door(?telic role) –Mary enjoyed [seeing] the garden(seeing...) author ⇔ read author ⇔ write

34. Logical Metonomy more examples –(enjoy) –Mary enjoyed [reading] the novel(reading) –!!The visitor enjoyed [verb] the door(?telic role) –Mary enjoyed [seeing] the garden(seeing...) multiple telic roles –Mary enjoyed inspecting the garden –Mary enjoyed visiting the garden –Mary enjoyed strolling through the garden –Mary enjoyed rollerblading in the garden –Mary enjoyed sitting in the garden –Mary enjoyed dozing in the garden

35. Logical Metonomy easily defeasible –He really enjoyed your book(reading) –He really enjoyed [reading] your book – –My goat eats anything. –He really enjoyed [verb] your book(reading) –(eating)

36. Logical Metonomy easily defeasible –My dog eats everything. –!He really enjoyed [verb] your shoe(eating) very different in character from typical syntactic gap-filling examples –not defeasible which report did you file without reading? cannot mean we’re asking about some report that you filed but someone else read –another example John is too stubborn [someone] to talk to [John] John is too stubborn [John] to talk to Bill

37. WordNet and Telic Role Computation example: –John enjoyed [verb] the cigarette(smoking)

38. WordNet and Telic Role Computation example –!John enjoyed [verb] the dirt(?telic role)

39. WordNet and Telic Role Computation example –!John enjoyed [verb] the wine(drinking)

40. WordNet and Telic Role Computation example –!John enjoyed [verb] the door(?telic role)

41. Points of Discussion issues –knowledge representation for semantic inferencing –do we have a network like WordNet? –how is it built? –is it wholly outside the “language faculty”?