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.
REF presents a full annotation of anaphora and coreference in biomedical text, but only noun phrases referring to biomedical entities are considered.
Statistical Anaphora Resolution in Biomedical Texts
International Conference On Computational Linguistics
Computer Science