NEED4Tweet: A Twitterbot for Tweets Named Entity Extraction and Disambiguation

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.

[1]  Maurice van Keulen,et al.  Unsupervised Improvement of Named Entity Extraction in Short Informal Context Using Disambiguation Clues , 2012, SWAIE.

[2]  Cong Yu,et al.  Searching Social Updates for Topic-centric Entities , 2011, VLDS.

[3]  Oren Etzioni,et al.  Entity Linking at Web Scale , 2012, AKBC-WEKEX@NAACL-HLT.

[4]  Karl Aberer,et al.  Entity-based Classification of Twitter Messages , 2012, Int. J. Comput. Sci. Appl..

[5]  Brian Locke.  Named Entity Recognition : Adapting to Microblogging , 2009 .

[6]  Brendan T. O'Connor,et al.  Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments , 2010, ACL.

[7]  Christian Bizer,et al.  DBpedia spotlight: shedding light on the web of documents , 2011, I-Semantics '11.

[8]  Maurice van Keulen,et al.  A Generic Open World Named Entity Disambiguation Approach for Tweets , 2013, KDIR/KMIS.

[9]  Aba-Sah Dadzie,et al.  Making Sense of Microposts (#MSM2013) Concept Extraction Challenge , 2013, #MSM.

[10]  Aba-Sah Dadzie,et al.  Making Sense of Microposts (#Microposts2014) Named Entity Extraction & Linking Challenge , 2014, #MSM.

[11]  Djoerd Hiemstra,et al.  Retrieving Web Pages Using Content, Links, URLs and Anchors , 2001, TREC.

[12]  Jason J. Jung.  Online named entity recognition method for microtexts in social networking services: A case study of twitter , 2012, Expert Syst. Appl..

[13]  Raquel Martínez Unanue,et al.  Unsupervised Real-Time Company Name Disambiguation in Twitter , 2012, ICWSM 2012.

[14]  Djoerd Hiemstra,et al.  Linear Co-occurrence Rate Networks (L-CRNs) for Sequence Labeling , 2014, SLSP.

[15]  Julio Gonzalo,et al.  Filter Keywords and Majority Class Strategies for Company Name Disambiguation in Twitter , 2011, CLEF.

[16]  Oren Etzioni,et al.  Named Entity Recognition in Tweets: An Experimental Study , 2011, EMNLP.

[17]  Bu-Sung Lee,et al.  TwiNER: named entity recognition in targeted twitter stream , 2012, SIGIR '12.

[18]  Gerhard Weikum,et al.  WWW 2007 / Track: Semantic Web Session: Ontologies ABSTRACT YAGO: A Core of Semantic Knowledge , 2022 .

[19]  Maurice van Keulen,et al.  TwitterNEED: A hybrid approach for named entity extraction and disambiguation for tweet* , 2015, Natural Language Engineering.