SenseLearner: Minimally Supervised Word Sense Disambiguation for All Words in Open Text

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This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the sense from WordNet. SenseLearner participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%.

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4 p.

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Mihalcea, Rada, 1974- & Faruque, Ehsanul 2004.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Engineering to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 109 times . More information about this paper can be viewed below.

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UNT College of Engineering

The UNT College of Engineering promotes intellectual and scholarly pursuits in the areas of computer science and engineering, preparing innovative leaders in a variety of disciplines. The UNT College of Engineering encourages faculty and students to pursue interdisciplinary research among numerous subjects of study including databases, numerical analysis, game programming, and computer systems architecture.

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Description

This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the sense from WordNet. SenseLearner participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%.

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4 p.

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  • Association for Computational Linguistics (ACL)/SIGLEX Senseval-3 Conference, 2004, Barcelona, Spain

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UNT Scholarly Works

The Scholarly Works Collection is home to materials from the University of North Texas community's research, creative, and scholarly activities and serves as UNT's Open Access Repository. It brings together articles, papers, artwork, music, research data, reports, presentations, and other scholarly and creative products representing the expertise in our university community.** Access to some items in this collection may be restricted.**

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  • 2004

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  • Jan. 31, 2011, 2:01 p.m.

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  • March 27, 2014, 1:05 p.m.

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Citations, Rights, Re-Use

Mihalcea, Rada, 1974- & Faruque, Ehsanul. SenseLearner: Minimally Supervised Word Sense Disambiguation for All Words in Open Text, paper, 2004; [Stroudsburg, Pennsylvania]. (digital.library.unt.edu/ark:/67531/metadc30961/: accessed March 29, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.