Expanding the Type Hierarchy with Nonlexical Concepts

  • Caroline Barrière
  • Fred Popowich
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1822)


Type hierarchies are important structures used in knowledge stores to enumerate and classify the entities from a domain of interest. The hierarchical structure establishes de facto a “similarity space” in which the elements of a same class are considered close semantically, as they share the properties of their superclass. An important task in Natural Language Processing (NLP) is sentence understanding. This task relies partly on comparing the words in the sentence among each other as well as to the words in previous sentences and to words in a knowledge store. A type hierarchy consisting of words and/or word senses can be useful to facilitate these comparisons and establish which words are semantically related. The problems of using a type hierarchy for evaluating semantic distance come from its dependency on the available words of a specific language, and on the arbitrariness of its classes and of its depth, which leads to the development of semantic distance measures giving arbitrary results. We propose a way to extend the type hierarchy, to give more flexibility to the “similarity space”, by including non-lexical concepts defined around relations other than taxonomic ones. We also suggest a method for discovering these non-lexical concepts in texts, and present some results.


Natural Language Processing Semantic Similarity Conceptual Space Word Sense Semantic Distance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Caroline Barrière
    • 1
  • Fred Popowich
    • 2
  1. 1.School of Information Technology and EngineeringUniversity of OttawaOttawaCanada
  2. 2.School of Computing ScienceSimon Fraser UniversityBurnabyCanada

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