@inproceedings{nguyen-etal-2008-challenges,
title = "Challenges in Pronoun Resolution System for Biomedical Text",
author = "Nguyen, Ngan and
Kim, Jin-Dong and
Tsujii, Jun{'}ichi",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Tapias, Daniel",
booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}`08)",
month = may,
year = "2008",
address = "Marrakech, Morocco",
publisher = "European Language Resources Association (ELRA)",
url = "https://preview.aclanthology.org/add-emnlp-2024-awards/L08-1071/",
abstract = "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."
}
Markdown (Informal)
[Challenges in Pronoun Resolution System for Biomedical Text](https://preview.aclanthology.org/add-emnlp-2024-awards/L08-1071/) (Nguyen et al., LREC 2008)
ACL