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Features and Augmented Grammars

Features and Augmented Grammars. Allen ’ s Chapter 4 J&M ’ s Chapter 11. Augmenting CFGs with Features. Certain linguistic constraints are not naturally described via CFGs Example: Number Agreement between constituents - “a boys” Possible to describe using refined CF rules:

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Features and Augmented Grammars

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  1. Features and Augmented Grammars Allen’s Chapter 4 J&M’s Chapter 11

  2. Augmenting CFGs with Features • Certain linguistic constraints are not naturally described via CFGs • Example: Number Agreement between constituents - “a boys” • Possible to describe using refined CF rules: NP-Sing --> ART-Sing N-Sing NP-Plural --> ART-Plural N-Plural • Much more natural to describe via a single feature Number in an augmented CF rule: NP --> ART N (only when Number1 = Number2)

  3. Feature Structures • Constituents can be defined as feature structures that map features to values • Features can be shared between constituents • Some basic features for English: – Number, Gender and Person agreement – Verb form features and sub-categorizations • Complex Feature Structures: Feature values can themselves be feature structures

  4. An Example ART1: (CAT ART ROOT a NUMBER s) Represents a particular use of word a Often summarized as: ART1: (ART ROOT a NUMBER s)

  5. Larger constituents: Representing an NP constituent for the phrase a fish NP1: (NP NUMBER s 1 (ART ROOT a NUMBER s) 2 (N ROOT fish NUMBER s))

  6. Feature Structure

  7. Augmented Rules (NP NUMBER ?n)  (ART NUMBER ?n) (N NUMBER ?n) *(NP 1 (ART NUMBER s) 2 (N NUMBER s)) *(NP NUMBER s 1 (ART NUMBER s) 2 (N NUMBER p))

  8. Using Variables to Express ambiguities (N ROOT fish NUMBER ?n) (N ROOT fish NUMBER ?b {s, p}) (N ROOT fish NUMBER {s, p})

  9. Person and Number Features

  10. PForm Feature

  11. Verb Sub categorizations:SUBCAT Feature

  12. SUBCAT Examples: (VP)  (V SUBCAT _np_vp:inf) (NP) (VP VFORM inf) (VP)  (V SUBCAT _np_pp:loc) (NP) (PP PFORM LOC)

  13. Binary Features Whether the constituent does or does not have a feature INV feature has two values + and – Jack Laughed has an INV feature with value – = (-INV) Did Jack Laugh has an INV feature with value + = (+INV)

  14. Morphological Analysis

  15. Sample Grammar (Abbreviated Form)

  16. Sample Grammar (Detailed Form)

  17. Parsing with Features • (NP AGR ?a)   (ART AGR ?a) (N AGR ?a) • (ART ROOT A AGR 3s) • (NP AGR 3s)   (ART AGR 3s) (N AGR 3s) • (NP AGR 3s)  (ART AGR 3s)  (N AGR 3s) • (N ROOT DOG1 AGR 3s) • (NP AGR 3s)  (ART AGR 3s) (N AGR 3s) 

  18. Parsing with Features • Given an arc A, and NEXT as the constituent following , and a new constituent X, which is used to extend A • Find an instantiation of variables such that all features specified in NEXT are found in X. • Create a new arc A’, which is a copy of A except for the instantiations of the variables determined in step 1 • Update A’ as usual in a Chart parser

  19. Parse Trees with Features

  20. Chart with Features

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