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Published on November 15, 2007

Author: Aric85

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Slide1:  Faculty of Computer Science Tony Abou-Assaleh, Nick Cercone, and Vlado Kešelj {taa,nick,vlado}@cs.dal.ca INTRODUCTION Motivation Head-driven Phrase Structure Grammar (HPSG) can represent both syntax and semantics Question Answering (QA) plays an important role in Natural Language Processing (NLP) Relaxed Unification enables HPSG to process data that is inconsistent, incomplete, and uncertain. Objectives Identify limitations of current QA systems Develop a framework to overcome these limitations Build a QA advanced prototype Objectively evaluate the prototype against other approaches Classical Unification Two terms, t and u, are unifiable if and only if there exists a substitution  such that t  = u . Relaxed Unification Relaxed Term consists of variables and sets of functions, where sets can be empty. Function arguments are relaxed terms. E.g. { f ( { a } , { h ( { b } ) } ) }. two terms, t and u, are always unifiable with a unifying substitution  such that t  = u . Application-specific correctness measure evaluates the result. RELAXED UNIFICATION HPSG AND QUESTION ANSWERING Query “How much could you rent a Volkswagen bug for in 1966?” Relevant Text “… you could rent a Volkswagen bug for $1 a day.” Answer “$1 a day.” EVALUATION Environment Text REtrieval Conference (TREC) Question Answering Track. Open-domain, closed-class questions. Shallow semantic analysis is some times required. Restricted QA: only factoid and definition questions. Approach Use an Information Retrieval (IR) search engine to locate relevant passages. Use HPSG to parse the question and generate a query. Use HPSG to parse the passage. Use relaxed unification to locate a query match in the passage. Compute the correctness of the result using a metric to rank the answers. References Abou-Assaleh, Tony and Cercone, Nick and Keselj, Vlado. Towards the Theory of Relaxed Unification. In Proceedings of the 14th International Symposium on Methodologies for Intelligent Systems, ISMIS 2003, volume LNAI 2871 of Lecture Notes in Computer Science, Springer, Maebashi City, Japan, October 28--31, 2003. Kešelj, Vlado. Question Answering using Unification-based Grammar. In Advances in Artificial Intelligence, AI 2001, volume LNAI 2056 of Lecture Notes in Computer Science, Springer, Ottawa, Canada, June 2001.

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