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    <responseDate>2026-10-13T00:41:10Z</responseDate>
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    <header >
    <identifier>10.57760/sciencedb.j00133.00726</identifier>
    <datestamp>2026-09-20T09:57:43Z</datestamp>
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  <dc:date>2026-09-20</dc:date>
  <dc:title>Contradictory statement recognition-fine-tuning training data</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.j00133.00726</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The original data of this data set come from: [1] Guarino G, Samet A, Cavallucci D. Patriz: A Framework for Mining TRIZ Contraventions in Patents [J]. Expert Systems with Applications, 2022,207: 117942.On this basis, this data set is processed and stored in the form of json. There are 3,200 patent data, of which 1,600 patent data contain contradictory statements and 1,600 patents have no contradictory statements.</dc:description>
  <dc:subject>patent; triz; contradiction</dc:subject>
  <dc:creator>Qu Qianwei</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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