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Register a new userTime, Tense and Aspect in Natural Language Database Interfaces
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Added by
Ion Androutsopoulos
Publication date
1998
fields
Informatics Engineering
and research's language is
English
Authors
I. Androutsopoulos
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Most existing natural language database interfaces (NLDBs) were designed to be used with database systems that provide very limited facilities for manipulating time-dependent data, and they do not support adequately temporal linguistic mechanisms (verb tenses, temporal adverbials, temporal subordinate clauses, etc.). The database community is becoming increasingly interested in temporal database systems, that are intended to store and manipulate in a principled manner information not only about the present, but also about the past and future. When interfacing to temporal databases, supporting temporal linguistic mechanisms becomes crucial. We present a framework for constructing natural language interfaces for temporal databases (NLTDBs), that draws on research in tense and aspect theories, temporal logics, and temporal databases. The framework consists of a temporal intermediate representation language, called TOP, an HPSG grammar that maps a wide range of questions involving temporal mechanisms to appropriate TOP expressions, and a provably correct method for translating from TOP to TSQL2, TSQL2 being a recently proposed temporal extension of the SQL database language. This framework was employed to implement a prototype NLTDB using ALE and Prolog.
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Over the past thirty years, there has been considerable progress in the design of natural language interfaces to databases. Most of this work has concerned snapshot databases, in which there are only limited facilities for manipulating time-varying information. The database community is becoming increasingly interested in temporal databases, databases with special support for time-dependent entries. We have developed a framework for constructing natural language interfaces to temporal databases, drawing on research on temporal phenomena within logic and linguistics. The central part of our framework is a logic-like formal language, called TOP, which can capture the semantics of a wide range of English sentences. We have implemented an HPSG-based sentence analyser that converts a large set of English queries involving time into TOP formulae, and have formulated a provably correct procedure for translating TOP expressions into queries in the TSQL2 temporal database language. In this way we have established a sound route from English to a general-purpose temporal database language.
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