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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

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Two Related Lexico-Syntactic Approaches to Entailment

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  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

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