Abstract
The presented (Question Answering) system uses clarification dialogues in order to disambiguate the possible meaning of user questions in natural language. The system will only query the user when commitment to some meaning is relevant for the final answer. When there are multiple different answers to a user query, the system initiates a clarification dialogue trying to ascertain the user’s intentions. The clarification question is always about a relevant property of a (user) discourse entity. The answer to the clarification question (its semantic representation) can be incorporated into the initial user question enabling its reinterpretation under the new constraints. This is developed in an integrated logic programming framework, based on constraint logic programming using the GnuProlog(-cx) language [3,7] and the ISCO framework [2] . The use of this LP framework allows the integration of Prolog-like inference mechanisms with classes and inheritance, constraint solving algorithms and provides the connection with relational databases, such as PostgreSQL.
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Quintano, L., Rodrigues, I.P. (2008). Question/Answering Clarification Dialogues. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_14
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DOI: https://doi.org/10.1007/978-3-540-88636-5_14
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