• DocumentCode
    1649542
  • Title

    Determining Relation Semantics by Mapping Relation Phrases to Knowledge Base

  • Author

    Fang Liu ; Yang Liu ; Guangyou Zhou ; Kang Liu ; Jun Zhao

  • Author_Institution
    Nat. Lab. of Pattern Recognition (NLPR), Inst. of Autom., Beijing, China
  • fYear
    2013
  • Firstpage
    420
  • Lastpage
    424
  • Abstract
    Open Information Extraction (Open IE) recognizes domain-independent relational triples from natural language texts but does not recognize the exact semantics of the triples. Nevertheless, relations in existing knowledge bases, like manually edited attributes in Wikipedia Info boxes, have provided the semantic meaning of open relations. Therefore, our goal is to bridge the gap between open relation phrases extracted by an Open IE system and a pre-defined attributes in knowledge base. This task is important for Information Extraction. In this paper, we proposed a novel approach to map relation phrases to attributes in knowledge base. We matched relational triples extracted from Wikipedia articles with attribute triples generated from Wikipedia Info boxes. Finally, our system expanded 509 Wikipedia attributes with a total of 2,527 phrases. Experiments show that the proposed approach can achieve an average precision of 0.88±0.02 over all mapped relation pairs.
  • Keywords
    Web sites; information retrieval; knowledge based systems; natural language processing; semantic Web; text analysis; Wikipedia Info boxes; Wikipedia articles; Wikipedia attributes; attribute triples; domain-independent relational triples; knowledge base attributes; knowledge bases; natural language texts; open IE system; open information extraction; open relation phrases; relation phrases mapping; relation semantics; semantic meaning; Electronic publishing; Encyclopedias; Information retrieval; Internet; Knowledge based systems; Semantics; Open Information Extraction; Relation Mapping; Wikipedia Infobox;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ACPR), 2013 2nd IAPR Asian Conference on
  • Conference_Location
    Naha
  • Type

    conf

  • DOI
    10.1109/ACPR.2013.55
  • Filename
    6778353