1 / 15

Two Related Lexico-Syntactic Approaches to Entailment

Two Related Lexico-Syntactic Approaches to Entailment. Vasile Rus Institute for Intelligent Systems Department of Computer Science http://www.cs.memphis.edu/~vrus. TODAY- Outline. General strategy Map T and H into lexico-syntactic graphs

taran
Download Presentation

Two Related Lexico-Syntactic Approaches to Entailment

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. Two Related Lexico-Syntactic Approaches to Entailment Vasile Rus Institute for Intelligent Systems Department of Computer Science http://www.cs.memphis.edu/~vrus

  2. TODAY- Outline • General strategy • Map T and H into lexico-syntactic graphs • Perform graph subsumption between graph-T and graph-H • Additive strategy • Not cascaded • Two approaches • Lexico-syntactic approach • Dependency-based approach • Results, Comparison, Conclusions

  3. The Two Approaches • Lexico-syntactic approach • Lexical component • Syntactic component • Dependencies derived from phrase-based parse trees • Negation • thesaurus • Dependency-based approach • Dependencies from MINIPAR • Lexical component by default • Postprocessing (thanks to Vivi Nastase) • To eliminate unused information • To retain only dependencies among content words

  4. Graph Subsumption • Map nodes and edges in H-graph to nodes and edges in T-graph • complex mapping based on • Named Entity Inferences: Overture Services Inc -- Overture • Word-level entailment / equivalence: take over – buy • Syntactic Info: • Yahoo is the agent of buying

  5. From Sentences to Graph Representation • vertices represent content words • edges represent dependencies • local dependencies (intra-phrase) are straightforwardly obtained from a parse tree • remote dependencies are obtained using an extended functional tagger • Or from MINIPAR (for the second approach)

  6. The Entailment Score • The score is so defined to be non-reflexive: • entail(T, H) ≠ entail(H,T) Score is also used as confidence

  7. The Parameters • the following parameters worked best on development α=.5 β =.5 γ=0

  8. Negation • Explicit • Clue phrases • no, not, neither … nor • shortened forms: ‘nt • Implicit • Antonymy in WordNet • Hypothetical sentences: “a possible visit by Clinton to China” does not entail “Clinton visited China” • a form of negation

  9. Results – Lexico-Syntactic Approach

  10. Comparison

  11. Conclusions • Lexical information significantly helps • The other components (synonymy, dependencies, negation) add value but not significantly

  12. Missed Opportunities • Linguistic Level • Five = 5 • Tuscany province = province of Tuscany • Current subsumption algorithm is weak • T: Besancon is the capital of France’s watch and clock-making industry and of high precision engineering. • H: Besancon is the capital of France. Solution: matching with more complex structures • World Knowledge

  13. More Conclusions • Our system is light • Good for interactive environment such as Intelligent Tutoring Systems • No training involved • Just development to tune few parameters

  14. One More Conclusion • It is not clear whether there is a difference among the two ways to obtain dependencies!

  15. Two Related Lexico-Syntactic Approaches to Entailment ! Thank you everyone

More Related