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Faculty of Computer Science Tony Abou-Assaleh, Nick Cercone, and Vlado Kešelj {taa,nick,vlado}@cs.dal.ca INTRODUCTION EVALUATION Abstract Motivation Environment – 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 RELAXED UNIFICATION Question answering is an important task of natural language processing. Unification-based grammars have emerged as formalisms for reasoning about natural text. Head-driven Phrase Structure Grammar is a unification-based grammar that is capable of representing syntax and semantics in a uniform fashion allowing one to reason about syntax and semantics simultaneously. Classical unification, on which the unificationbased grammars rely, is strict in the sense that it requires a perfect agreement between the terms being unified. In practise, data is seldom error-free and can contain inconsistent information. The theory of relaxed unification is a new theory that relaxes the constraints of the classical unification. Relaxed unification tolerates errors and inconsistencies in the data and facilitates reasoning under uncertainty. We use the relaxed unification formalism in the head-driven phrase structure grammar to build a question-answering advanced prototype that addresses some of the pitfalls of the current questionanswering systems. – 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. Input Classical Unification – Two terms, t and u, are unifiable if and only if there exists a substitution such that t = u . HPSG AND QUESTION ANSWERING Documents Collection – “How much could you rent a Volkswagen bug for in 1966?” Relevant Text – “… you could rent a Volkswagen bug for $1 a day.” – two terms, t and u, are always unifiable with a unifying substitution such that t = u . – Application-specific correctness measure evaluates the result. Ranked Answers Question Query 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 } ) } ) }. Output Answer – “$1 a day.” Extraction IR Search Engine HPSG Parser Relevant Passages Query HPSG Parser Ranked Matches Evaluation Parsed Passages Relaxed Unification Matches 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.