Bootstrapping for named entity tagging using concept-based seeds

Cheng Niu; Wei Li; Jihong Ding; Rohini K. Srihari

Bootstrapping for named entity tagging using concept-based seeds

Cheng Niu
, Wei Li
, Jihong Ding
, Rohini K. Srihari

Department of Computer Science and Engineering

Cymfony Inc

Research output: Contribution to conference › Paper › peer-review

2 Scopus citations

Abstract

A novel bootstrapping approach to Named Entity （NE）tagging using concept-based seeds and successive learners is presented. This approach only requires a few common noun or pronoun seeds that correspond to the concept for the targeted NE, e.g. he/she/man/woman for PERSON NE. The bootstrapping procedure is implemented as training two successive learners. First, decision list is used to learn the parsing-based NE rules. Then, a Hidden Markov Model is trained on a corpus automatically tagged by the first learner. The resulting NE system approaches supervised NE performance for some NE types.

Original language	English
Pages	73-75
Number of pages	3
State	Published - 2003
Event	2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, HLT-NAACL 2003 - Edmonton, Canada Duration: May 27 2003 → Jun 1 2003

Conference

Conference	2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, HLT-NAACL 2003
Country/Territory	Canada
City	Edmonton
Period	05/27/03 → 06/1/03

Cite this

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title = "Bootstrapping for named entity tagging using concept-based seeds",

abstract = "A novel bootstrapping approach to Named Entity （NE）tagging using concept-based seeds and successive learners is presented. This approach only requires a few common noun or pronoun seeds that correspond to the concept for the targeted NE, e.g. he/she/man/woman for PERSON NE. The bootstrapping procedure is implemented as training two successive learners. First, decision list is used to learn the parsing-based NE rules. Then, a Hidden Markov Model is trained on a corpus automatically tagged by the first learner. The resulting NE system approaches supervised NE performance for some NE types.",

author = "Cheng Niu and Wei Li and Jihong Ding and Srihari, \{Rohini K.\}",

note = "Publisher Copyright: {\textcopyright} HLT-NAACL 2003.All right reserved.; 2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, HLT-NAACL 2003 ; Conference date: 27-05-2003 Through 01-06-2003",

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language = "English",

pages = "73--75",

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TY - CONF

T1 - Bootstrapping for named entity tagging using concept-based seeds

AU - Niu, Cheng

AU - Li, Wei

AU - Ding, Jihong

AU - Srihari, Rohini K.

PY - 2003

Y1 - 2003

N2 - A novel bootstrapping approach to Named Entity （NE）tagging using concept-based seeds and successive learners is presented. This approach only requires a few common noun or pronoun seeds that correspond to the concept for the targeted NE, e.g. he/she/man/woman for PERSON NE. The bootstrapping procedure is implemented as training two successive learners. First, decision list is used to learn the parsing-based NE rules. Then, a Hidden Markov Model is trained on a corpus automatically tagged by the first learner. The resulting NE system approaches supervised NE performance for some NE types.

AB - A novel bootstrapping approach to Named Entity （NE）tagging using concept-based seeds and successive learners is presented. This approach only requires a few common noun or pronoun seeds that correspond to the concept for the targeted NE, e.g. he/she/man/woman for PERSON NE. The bootstrapping procedure is implemented as training two successive learners. First, decision list is used to learn the parsing-based NE rules. Then, a Hidden Markov Model is trained on a corpus automatically tagged by the first learner. The resulting NE system approaches supervised NE performance for some NE types.

UR - https://www.scopus.com/pages/publications/84994071873

M3 - Paper

AN - SCOPUS:84994071873

SP - 73

EP - 75

T2 - 2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, HLT-NAACL 2003

Y2 - 27 May 2003 through 1 June 2003

ER -

Bootstrapping for named entity tagging using concept-based seeds

Abstract

Conference

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