Gathering lexical linked data and knowledge patterns from FrameNet

  • Authors:
  • Andrea Giovanni Nuzzolese;Aldo Gangemi;Valentina Presutti

  • Affiliations:
  • University of Bologna/CNR, Bologna, Italy;CNR, Rome, Italy;CNR, Rome, Italy

  • Venue:
  • Proceedings of the sixth international conference on Knowledge capture
  • Year:
  • 2011

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Abstract

FrameNet is an important lexical knowledge base featuring cognitive plausibility, and grounded in a large corpus. Besides being actively used by the NLP community, frames are a great source of knowledge patterns once converted into a knowledge representation language. In this paper we present our experience in converting the 1.5 XML version of FrameNet into RDF datasets published on the Linked Open Data cloud, which are interoperable with WordNet and other resources. In the conversion we have used Semion, a new tool that allows a rule-based, customized pipeline from XML to RDF and OWL data. In addition, we introduce a method to select and refactor part of the information related to frames as full-fledged OWL knowledge patterns. This last result has required non-trivial assumptions on how to interpret FrameNet relations as formal knowledge.