Conference paper Open Access

WinoReg: A New Faster and More Accurate Metric of Hardness for Winograd Schemas

Nicos Isaak; Loizos Michael

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      <creatorName>Nicos Isaak</creatorName>
      <affiliation>Open University of Cyprus</affiliation>
      <creatorName>Loizos Michael</creatorName>
      <affiliation>Open University of Cyprus &amp; Research Center on Interactive Media, Smart Systems, and Emerging Technologies</affiliation>
    <title>WinoReg: A New Faster and More Accurate Metric of Hardness for Winograd Schemas</title>
    <date dateType="Issued">2020-04-27</date>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.29007/wl4b</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf"></relatedIdentifier>
  <version>Accepted pre-print</version>
    <rights rightsURI="">Creative Commons Attribution Non Commercial No Derivatives 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;The Winograd Schema Challenge (WSC), the task of resolving pronouns in certain carefully-structured sentences, has received considerable interest in the past few years as an alternative to the Turing Test. In our recent work we demonstrated the plausibility of&lt;br&gt;
using commonsense knowledge, automatically acquired from raw text in English Wikipedia, towards computing a metric of hardness for a limited number of Winograd Schemas. In this work we present WinoReg, a new system to compute hardness of Winograd&lt;br&gt;
Schemas, by training a Random Forest classier over a rich set of features identied in relevant WSC works in the literature. Our empirical study shows that this new system is considerably faster and more accurate compared to the system proposed in our earlier&lt;br&gt;
work, making its use as part of other WSC-based systems feasible.&lt;/p&gt;</description>
    <description descriptionType="Other">This work has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement  No 739578 and under Grant Agreement No 823783 and the Government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination and Development.</description>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/823783/">823783</awardNumber>
      <awardTitle>WeNet - The Internet of US</awardTitle>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/739578/">739578</awardNumber>
      <awardTitle>Research Center on Interactive Media, Smart System and Emerging Technologies</awardTitle>
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