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What KL-ONE lookalikes need to cope with natural language

Scope and aspect of plural noun phrases

  • III. Sorts And Types In Natural Language (Understanding) Systems
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Sorts and Types in Artificial Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 418))

Abstract

One of the major drawbacks of current NL processing systems is the lack of an adequate representation of plurals and of the means to reason about them. On one hand, this is due to the fact that current knowledge representation languages like KL-ONE lookalikes do not provide well-suited representational means either to describe sets, subsets, and elements or to deal with the respective relations or use them in specially tailored inference systems.

On the other hand, workers in linguistics provide some (although conflicting) theories about the referential, cardinal, and quantificational aspects of the meaning of plural noun phrases, namely Discourse Semantics Theory, Generalized Quantifier Theory, and Referential Net Theory.

Our goal in the present work is to extend KL-ONE lookalikes by set maintenance and to support the use of sets in an NL system with a well-suited linguistic theory.

The work presented here is being supported by the German Science Foundation (DFG) in its Special Collaborative Program on AI and Knowledge-Based Systems (SFB 314), project N1 (XTRA).

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Author information

Authors and Affiliations

  1. FR 10.2 Dept. of Computer Science IV, University of Saarbrücken, Im Stadtwald 15, 6600, Saarbrücken 11, West Germany

    Jürgen Allgayer & Carola Reddig-Siekmann

Authors
  1. Jürgen Allgayer
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  2. Carola Reddig-Siekmann
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Karl Hans Bläsius Ulrich Hedtstück Claus-Rainer Rollinger

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© 1990 Springer-Verlag Berlin Heidelberg

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Allgayer, J., Reddig-Siekmann, C. (1990). What KL-ONE lookalikes need to cope with natural language. In: Bläsius, K.H., Hedtstück, U., Rollinger, CR. (eds) Sorts and Types in Artificial Intelligence. Lecture Notes in Computer Science, vol 418. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-52337-6_27

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  • DOI: https://doi.org/10.1007/3-540-52337-6_27

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  • Print ISBN: 978-3-540-52337-6

  • Online ISBN: 978-3-540-46965-0

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