COMP 4060 Natural Language Processing

1. COMP 4060 Natural Language Processing Feature Structures and Unification

2. Feature Structures - General • Feature structures describe linguistic attributes or features like number, personassociated with words or syntactic constituents like noun phrase. • Feature structures are sets of features and values, e.g. hat [Number sing ] buys [Person 3 ] [Number sing ]

3. Feature Structures - Agreement Feature structures can be collected in one ‘variable’ called agreement. buys agreement [Person 3] [Number sing]

4. Feature Structures, Grammar, Parsing Feature Structures • describe additional syntactic-semantic information, like category, person, number, e.g. goes <verb, 3rd, singular> • specifyfeature structure constraints (agreements) as part of the grammar rules • during parsing, check agreements of feature structures (unification) example S → NP VP <NP number> = <VP number> S → NP VP <NP agreement> = <VP agreement>

5. Feature Structures as Constraints Ungrammatical sentences like “He go” or “We goes” can be excluded using feature constraints. example S → NP VP <NP agreement> = <VP agreement> S → NP VP <NP number> = <VP number> <NP person> = <VP person>

6. Feature Structures and Categories Add to feature structure category cat: buyscatverb agreement [Person 3 ] [Number sing]

7. Feature Structures and Unification Compare and combine feature structures: he buys buyscatverb agreement [Person 3] [Number sing] hecatnoun agreement [Person 3] [Number sing]

8. Unification of Feature Structures Agreement is checked by the unification operation according to the following rules: [featurei valuei] |_| [featurei valuei] = [featurei valuei] [featurei valuei] |_| [featurei valuej] = fail if valueivaluej [featurei valuei] |_| [featureiundef.] = [featurei valuei] [featurei valuei] |_| [featurej valuej] = featurei valuei featurej valuej if featurei featurej

9. "Inheritance" of Feature Structures Feature structures are "inherited" during parsing or generation, using the feature structure of the head of a phrase: NP  det Nom NP <fivi>i=1,..,n det Nom<fivi>i=1,..,n Nom <fivi>i=1,..,n pre-Nom Nom<fivi>i=1,..,npost-Nom Complex feature structures are often referenced through identifying numbers. Constraints on feature structures can be checked using these references; and the same feature structure can be used in different parts of the parse tree through reference. head

10. Features and Subcategorization 1 NP modifiers or Verb complements central noun + modifiers +agreement central verb+complements+agreements “... the man who chased the cat out of the house ...” “... the man chased the barking dog who bit him ...” Agreements are passed on / inherited within phrases, e.g. agreement of VP derived from Head-Verb of VP: <VP agreement> determined by <Verb agreement> <NP agreement> determined by <Nom agreement>

11. Features and Subcategorization 2 NP modifiers: central noun + modifiers +agreement “... the man who chased the cat out of the house ...” NP -<agreement> determined by man-<agreement> Verb complements: central verb+complements+agreements “... the man chased the barking dog who bit him ...” VP-<agreement> determined by chased-<agreement>