2005 DocumentAnnotationAndOntologyPop

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Subject Headings: Linguistically Grounded Ontology. Knowledge acquisition tool, Knowledge extraction from text, Knowledge capture for the Semantic Web, Knowledge capture using natural language processing, Method for ontology population, Semantic Web.

Notes

  • It deals with ontology population from linguistic extractions.
  • It uses knowledge acquisition rules are used to map concept tree nodes to ontology instances.
  • Its nodes are the result of extraction and annotation of documents.
  • It describes how to connect: 1) modeling domain knowledge using ontological concepts and 2) linguistic extractions.
  • It reports results in the legal domain and show how an ontology can be populated from annotated documents.

Cited By

Quotes

Abstract

In this paper, we present a workbench for semi-automatic ontology population from textual documents. It provides an environment for mapping the linguistic extractions with the domain ontology thanks to knowledge acquisition rules. Those rules are activated when a pertinent linguistic tag is reached. Those linguistic tags are then mapped to a concept, one of its attributes or even a semantic relation between several concepts. The rules instantiate these concepts, attributes and relations in the knowledge base constrained by the domain ontology. This paper deals with the underlying knowledge capture process and presents the first experiments realized on a real client application from the legal publishing domain.


References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2005 DocumentAnnotationAndOntologyPopFlorence Amardeilh
Philippe Laublet
Jean-Luc Minel
Document Annotation and Ontology Population from Linguistic Extractionshttp://mondeca.com/content/download/454/3431/file/fp66 amardeilh.pdf10.1145/1088622.1088651