NEED4Tweet: A Twitterbot for Tweets Named Entity Extraction and Disambiguation

Mena Badieh Habib, Maurice van Keulen

Research output: Contribution to conferencePaper

5 Citations (Scopus)
25 Downloads (Pure)

Abstract

In this demo paper, we present NEED4Tweet, a Twitterbot for named entity extraction (NEE) and disambiguation (NED) for Tweets. The straightforward application of state-of-the-art extraction and disambiguation approaches on informal text widely used in Tweets, typically results in significantly degraded performance due to the lack of formal structure; the lack of sufficient context required; and the seldom entities involved. In this paper, we introduce a novel framework that copes with the introduced challenges. We rely on contextual and semantic features more than syntactic features which are less informative. We believe that disambiguation can help to improve the extraction process. This mimics the way humans understand language.
Original languageEnglish
Pages-
Number of pages6
Publication statusPublished - Jul 2015
Event53rd Annual Meeting of the Association for Computational Linguistics 2015 - China National Convention Center, Beijing, China
Duration: 26 Jul 201531 Jul 2015
Conference number: 53
http://acl2015.org/

Conference

Conference53rd Annual Meeting of the Association for Computational Linguistics 2015
Abbreviated titleACL 2015
CountryChina
CityBeijing
Period26/07/1531/07/15
Internet address

Keywords

  • METIS-312606
  • IR-96449
  • EWI-26015

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    Habib, M. B., & van Keulen, M. (2015). NEED4Tweet: A Twitterbot for Tweets Named Entity Extraction and Disambiguation. -. Paper presented at 53rd Annual Meeting of the Association for Computational Linguistics 2015, Beijing, China.