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UNED at PASCAL RTE-2 Challenge IR&NLP Group at UNED nlp.uned.es Jesús Herrera Anselmo Peñas Álvaro Rodrigo Felisa Verdejo
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Outline Underlying thesis Overall architecture Lexical Entailment Entailment decision Results Conclusion & future Work
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Underlying Thesis Compositional meaning of the statements All “components” of the hypothesis must be entailed Definition of “statement component” Our Roadmap: 1. Word & multiword level 2. NE, numeric & temporal expressions level 3. Phrase level & paraphrase (in progress)
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Overall Architecture Dependency Parser NE Recognizer Linguistic Processing WN-based Entailment NE Entailment Lexical Entailment Decision Sentence Matching Sentence Entailment
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WN-based Lexical Entailment WordNet based entailment Synonymy Hyponymy( Herrera et al. 2005) Antonymy Verb Entailment Part meronymyItaly entails Europe PertainymyItalian entails Italy (Glosses) Search of entailment paths Depth Breadth Path Length
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WN-based Lexical Entailment 10% 1% 3%
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Numerical Entailment 17 million citizensMore than 15 million people TextHypothesis recognize Lower bound: 17,000,000 Upper bound: 17,000,000 Unit: citizen Lower bound: 15,000,000 Upper bound: infinite Unit: person normalize Entailment is TRUE if [17,000,000.. 17,000,000] [15,000,000.. Infinite) and citizen entails person entailment
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Numerical Entailment
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Entailment Decision Support Vector Machines % of hypothesis lemmas entailed % of hypothesis words coincidence Existence of numeric expressions not entailed in the hypothesis Existence of NE not entailed in the hypothesis (after submission)
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Results Run 1Run 2 (+word coincidence) (+NE entailment) IE49.0%52.0%51.0% QA56.5%52.0%53.5% IR64.5%57.0%63.5% SUM69.0%74.5%74.0% Overall59.75%58.87%60.5%
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Conclusion & Future Work WN is nice but doesn’t help too much with an indiscriminate use (Check by source task) Different processing for each source task NE & numerical entailment seem promising Pay more attention to the entailment decision Future Phrase level entailment Paraphrase
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