This paper presents a probabilistic model for resolution of non-pronominal anaphora in biomedical texts. The model seeks to find the antecedents of anaphoric expressions, both coreferent and associative ones, and also to identify discourse-new expressions. We consider only the noun phrases referring to biomedical entities. The model reaches state-of-the art performance: 56--69% precision and 54--67% recall on coreferent cases, and reasonable performance on different classes of associative cases.
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Gasperin et al. (2008) studied this question.