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LREC
2008

Challenges in Pronoun Resolution System for Biomedical Text

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Challenges in Pronoun Resolution System for Biomedical Text
This paper presents our findings on the feasibility of doing pronoun resolution for biomedical texts, in comparison with conducting pronoun resolution for the newswire domain. In our experiments, we built a simple machine learning-based pronoun resolution system, and evaluated the system on three different corpora: MUC, ACE, and GENIA. Comparative statistics not only reveal the noticeable issues in constructing an effective pronoun resolution system for a new domain, but also provides a comprehensive view of those corpora often used for this task.
Ngan Nguyen, Jin-Dong Kim, Jun-ichi Tsujii
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where LREC
Authors Ngan Nguyen, Jin-Dong Kim, Jun-ichi Tsujii
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