1 / 11

Just-in-time Subgrammar Extraction for HPSG

Just-in-time Subgrammar Extraction for HPSG. Vlado Keselj Graduate Student Conference Faculty of Mathematics University of Waterloo June 26, 2001. NL text =========== =========== ===========. NL grammar. subgrammar extraction. parser. subgrammar. parsing results.

rhett
Download Presentation

Just-in-time Subgrammar Extraction for HPSG

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Just-in-time Subgrammar Extraction for HPSG • Vlado Keselj • Graduate Student Conference • Faculty of Mathematics • University of Waterloo • June 26, 2001

  2. NL text =========== =========== =========== NL grammar subgrammar extraction parser subgrammar parsing results What is "just-in-time subgrammar extraction”

  3. Motivation • Subgrammar extraction is defined within the framework of grammar modularity. • managing complexity • parsing efficiency • context-based disambiguation

  4. Subgrammar Definition Sentence: s  * G(s)={(s,p1),…,(s,pn)} Grammar: Subgrammar: any partial order: G1G2 implies such that: G1G2 s* G1(s) G2 (s)

  5. Subgrammar Extraction Problem Given a grammar G and a set of words W Í S, find a minimal grammar G1 with the respect to a subgrammar relation £ such that: "sÎW* G(s) = G1(s) There can be no minimal grammars, or more than one.

  6. Subgrammar Extraction for CFGs Context-Free Grammar: (V, S, P, S) Subgrammar definition: G1£ G2 iff V1 Í V2, S1 Í S2, P1Í P2, S1=S2 Recipe for CFGs: 1. S ¬ S Ç W 2. Apply the algorithm for removing useless symbols* ( O(n3) time) *E.g., Aho Ullman 1979

  7. sentence noun verb 2 H: H: H: 2 P: 3 P: 3 AGR: 1 1 AGR: AGR: 1 P: 3 N: sg N: sg N: sg G: m G: m G: m noun H: verb AGR: P: 3 H: AGR: N: sg P: 3 G: m N: sg He writes. HPSG Grammars

  8. 3-SAT problem: (p Ú q ÚØr) Ù (ØqÚ rÚØs) Ù (ØpÚ qÚ s) t1 t2 (p Ú q ÚØr) (Øq Ú r Ú Øs) p: t q: f ASGN: ASGN: t1 t2 (p Ú q ÚØr) (Øq Úr Ú Øs) q: t r: t ASGN: ASGN: t1 t2 (p Ú q ÚØr) (Øq Ú r Ú Øs) r: f s: f ASGN: ASGN: start t1 t2 t3 Ù Ù 1 1 1 1 ASGN: ASGN: ASGN: ASGN: NP Completeness for HPSGs

  9. satisfied for: p=true q=false s=true (pÚ q ÚØr) Ù (ØqÚ r ÚØs) Ù (Øp Ú q Ús) t1 t2 (p Ú q ÚØr) (Øq Ú r Ú Øs) p: t q: f ASGN: ASGN: t1 t2 (p Ú q ÚØr) (Øq Ú r Ú Øs) q: t r: t ASGN: ASGN: t1 t2 (p Ú q ÚØr) (Øq Ú r Ú Øs) r: f s: f ASGN: ASGN: start t1 t1 t1 1 1 1 1 ASGN: p: t ASGN: p: t ASGN: p: t ASGN: p: t Ù Ù q: f q: f q: f q: f s: t s: t s: t s: t NP Completeness for HPSG (continued)

  10. typeX typeY1 typeY2 ... ... ... ... typeX typeY1 typeY2 ... An Approximate Efficient Solution for HPSGs 1. remove all features from G and obtain G1 E.g., a rule: is mapped to: 2. apply subgrammar extraction to G1 and obtain G2 3. recover features in G2 and obtain the solution G3 Running time complexity: O(size(G) . |Rule|)

  11. Overview • notion of subgrammar • notion of subgrammar extraction • efficient algorithm for CFGs • NP completeness for HPSGs • an approximate solution for HPSGs

More Related