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Frame semantic tree kernels for social network extraction from text

  • Apoorv Agarwal Balasubramanian
  • , Sriramkumar Balasubramanian
  • , Anup Kotalwar
  • , Jiehan Zheng
  • , Owen Rambow

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

In this paper, we present work on extracting social networks from unstructured text. We introduce novel features derived from semantic annotations based on FrameNet. We also introduce novel semantic tree kernels that help us improve the performance of the best reported system on social event detection and classification by a statistically significant margin. We show results for combining the models for the two aforementioned subtasks into the overall task of social network extraction. We show that a combination of features from all three levels of abstractions (lexical, syntactic and semantic) are required to achieve the best performing system.

Original languageEnglish
Title of host publication14th Conference of the European Chapter of the Association for Computational Linguistics 2014, EACL 2014
PublisherAssociation for Computational Linguistics (ACL)
Pages211-219
Number of pages9
ISBN (Print)9781632663962
StatePublished - 2014
Event14th Conference of the European Chapter of the Association for Computational Linguistics 2014, EACL 2014 - Gothenburg, Sweden
Duration: Apr 26 2014Apr 30 2014

Publication series

Name14th Conference of the European Chapter of the Association for Computational Linguistics 2014, EACL 2014

Conference

Conference14th Conference of the European Chapter of the Association for Computational Linguistics 2014, EACL 2014
Country/TerritorySweden
CityGothenburg
Period04/26/1404/30/14

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