Named Entity Extraction and Linking Challenge: University of Twente at Microposts2014

Mena B. Habib; Maurice Van Keulen; Zhemin Zhu

Named Entity Extraction and Linking Challenge: University of Twente at Microposts2014

Mena B. Habib, Maurice Van Keulen, Zhemin Zhu

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

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Abstract

Twitter is a potentially rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing (NLP) tasks. In this paper we present a hybrid approach for Named Entity Extraction (NEE) and Linking (NEL) for tweets. Although NEE and NEL are two topics that are well studied in literature, almost all approaches treated the two problems separately. We believe that disambiguation (linking) could help improving the extraction process. We call this potential for mutual improvement, the reinforcement effect. It mimics the way humans understand natural language. Furthermore, our proposed approaches handles uncertainties involved in the two processes by considering possible alternatives.

Original language	English
Title of host publication	Proceedings of the Microposts2014 NEEL Challenge
Publication status	Published - 2014
Externally published	Yes

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title = "Named Entity Extraction and Linking Challenge: University of Twente at Microposts2014",

abstract = "Twitter is a potentially rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing (NLP) tasks. In this paper we present a hybrid approach for Named Entity Extraction (NEE) and Linking (NEL) for tweets. Although NEE and NEL are two topics that are well studied in literature, almost all approaches treated the two problems separately. We believe that disambiguation (linking) could help improving the extraction process. We call this potential for mutual improvement, the reinforcement effect. It mimics the way humans understand natural language. Furthermore, our proposed approaches handles uncertainties involved in the two processes by considering possible alternatives.",

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year = "2014",

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T1 - Named Entity Extraction and Linking Challenge: University of Twente at Microposts2014

AU - Habib, Mena B.

AU - Keulen, Maurice Van

AU - Zhu, Zhemin

PY - 2014

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N2 - Twitter is a potentially rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing (NLP) tasks. In this paper we present a hybrid approach for Named Entity Extraction (NEE) and Linking (NEL) for tweets. Although NEE and NEL are two topics that are well studied in literature, almost all approaches treated the two problems separately. We believe that disambiguation (linking) could help improving the extraction process. We call this potential for mutual improvement, the reinforcement effect. It mimics the way humans understand natural language. Furthermore, our proposed approaches handles uncertainties involved in the two processes by considering possible alternatives.

AB - Twitter is a potentially rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing (NLP) tasks. In this paper we present a hybrid approach for Named Entity Extraction (NEE) and Linking (NEL) for tweets. Although NEE and NEL are two topics that are well studied in literature, almost all approaches treated the two problems separately. We believe that disambiguation (linking) could help improving the extraction process. We call this potential for mutual improvement, the reinforcement effect. It mimics the way humans understand natural language. Furthermore, our proposed approaches handles uncertainties involved in the two processes by considering possible alternatives.

M3 - Conference article in proceeding

BT - Proceedings of the Microposts2014 NEEL Challenge

ER -

Named Entity Extraction and Linking Challenge: University of Twente at Microposts2014

Abstract

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