Download presentation
Presentation is loading. Please wait.
1
Christel Kemke 2007/08 COMP 4060 Natural Language Processing Feature Structures and Unification
2
2007/08 Christel Kemke Feature Structures - General Feature structures describe linguistic attributes or features like number, person associated with words or syntactic constituents like noun phrase. Feature structures are sets of features and values, e.g. hat[Numbersing ] buys[Person 3 ] [Numbersing ]
3
2007/08 Christel Kemke Feature Structures - Agreement Feature structures can be collected in one ‘variable’ called agreement. buys agreement [Person 3] [Number sing]
4
2007/08 Christel Kemke Feature Structures, Grammar, Parsing Feature Structures describe additional syntactic-semantic information, like category, person, number, e.g. goes specify feature structure constraints (agreements) as part of the grammar rules during parsing, check agreements of feature structures (unification) example S → NP VP =
5
2007/08 Christel Kemke Feature Structures as Constraints Ungrammatical sentences like “He go” or “We goes” can be excluded using feature constraints. example S → NP VP = =
6
2007/08 Christel Kemke Add to feature structure category cat: buys cat verb agreement [Person 3 ] [Number sing] Feature Structures and Categories
7
2007/08 Christel Kemke Compare and combine feature structures: he buys buys cat verb agreement [Person 3] [Number sing] he cat noun agreement [Person 3] [Number sing] Feature Structures and Unification
8
2007/08 Christel Kemke Unification of Feature Structures Agreement is checked by the unification operation according to the following rules: [feature i value i ] |_| [feature i value i ] = [feature i value i ] [feature i value i ] |_| [feature i value j ] = failif value i value j [feature i value i ] |_| [feature i undef.] = [feature i value i ] [feature i value i ] |_| [feature j value j ] = feature i value i feature j value j if feature i feature j
9
2007/08 Christel Kemke "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 i=1,..,n det Nom i=1,..,n Nom i=1,..,n pre-Nom Nom i=1,..,n post-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
2007/08 Christel Kemke 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: determined by
11
2007/08 Christel Kemke Features and Subcategorization 2 NP modifiers: central noun + modifiers + agreement “... the man who chased the cat out of the house...” NP - determined by man - Verb complements: central verb + complements + agreements “... the man chased the barking dog who bit him...” VP- determined by chased-
Similar presentations
© 2024 SlidePlayer.com Inc.
All rights reserved.