Extraction of Relation Descriptors for Portuguese Using Conditional Random Fields

  • Sandra Collovini
  • Lucas Pugens
  • Aline A. Vanin
  • Renata Vieira
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8864)

Abstract

An important task in Information Extraction is Relation Extraction. Relation Extraction (RE) is the task of detecting and characterizing the semantic relations between entities in the text. This work proposes a new process for the extraction of any relation descriptors between Named Entities (NEs) in the Organization domain, for the Portuguese language, using the Conditional Random Fields (CRF) model. For example, from the following sentence fragment “Microsoft headquartered in Redmond, […]”, we can extract the relation descriptor “headquartered-in”, that relates the NEs “Microsoft” and “Redmond”. We evaluated different features configurations for CRF; the best results were obtained with the inclusion of the semantic feature based on the NE category, since this feature could express, in a better way, the kind of relationship between the pair of NEs we want to identify. The proposed process achieved F-measure rates of 45 % and 53 %, considering the extraction of complete and partial matching, respectively.

Keywords

Information extraction Relation extraction Named entity Named entity recognition Natural language processing Conditional random fields 
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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Sandra Collovini
    • 1
  • Lucas Pugens
    • 1
  • Aline A. Vanin
    • 1
  • Renata Vieira
    • 1
  1. 1.Pontifícia Universidade Católica do Rio Grande do Sul - PUCRSPorto AlegreBrazil

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