PolyUCOMP-CORE TYPED: Computing Semantic Textual Similarity using Overlapped Senses

Jian Xu, Qin Lu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


c 2013 Association for Computational Linguistics The Semantic Textual Similarity (STS) task aims to exam the degree of semantic equivalence between sentences (Agirre et al., 2012). This paper presents the work of the Hong Kong Polytechnic University (PolyUCOMP) team which has participated in the STS core and typed tasks of SemEval-2013. For the STS core task, the PolyUCOMP system disambiguates words senses using contexts and then determine sentence similarity by counting the number of senses they shared. For the STS typed task, the string kernel (Lodhi et al., 2002) is used to compute similarity between two entities to avoid string variations in entities.
Original languageEnglish
Title of host publication*SEM 2013 - 2nd Joint Conference on Lexical and Computational Semantics
PublisherAssociation for Computational Linguistics (ACL)
Number of pages6
ISBN (Electronic)9781937284480
Publication statusPublished - 1 Jan 2013
Event2nd Joint Conference on Lexical and Computational Semantics, *SEM 2013 - Atlanta, United States
Duration: 13 Jun 201314 Jun 2013


Conference2nd Joint Conference on Lexical and Computational Semantics, *SEM 2013
CountryUnited States

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Theoretical Computer Science

Cite this