1 Ocak 2018 Konferans bildirisi Açık Erişim

Ak, Koray; Bakay, Ozge; Yildiz, Olcay Taner

DataCite XML

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/32779</identifier>
  <creators>
    <creator>
      <creatorName>Ak, Koray</creatorName>
      <givenName>Koray</givenName>
      <familyName>Ak</familyName>
      <affiliation>Isik Univ, Dept Comp Engn, Istabul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Bakay, Ozge</creatorName>
      <givenName>Ozge</givenName>
      <familyName>Bakay</familyName>
      <affiliation>Bogazici Univ, Dept Linguist, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Yildiz, Olcay Taner</creatorName>
      <givenName>Olcay Taner</givenName>
      <familyName>Yildiz</familyName>
      <affiliation>Isik Univ, Dept Comp Engn, Istabul, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Comparison Of Turkish Proposition Banks By Frame Matching</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2018</publicationYear>
  <dates>
    <date dateType="Issued">2018-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/32779</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.81043/aperta.32778</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.81043/aperta.32779</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">By indicating semantic relations between a predicate and its associated participants in a sentence and identifying the role-bearing constituents, SRL provides an extensive dataset to understand natural languages and to enhance several NLP applications such as information retrieval, machine translation, information extraction, and question answering. The availability of large resources and the development of statistical machine learning methods have increased the studies in the field of SRL. One of the widely-used semantic resources applied for multiple languages is PropBank. In this paper, PropBanks applied for Turkish are compared by checking semantic roles in the frame files of matched verb senses. As this integrated lexical resource for Turkish is aimed to be used in a multilingual resource along with English, creation of an inclusive lexical resource for Turkish is of great importance.</description>
  </descriptions>
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