Improving anaphora resolution by identifying animate entities in texts

Some references to human beings can be identified in English texts using named entity (Chinchor, 1997) and pronoun recognition but in some genres this still leaves a large number of references to people unidentified. The remaining noun phrases have no overt marking as to their animacy and clues as to the appropriate classification of a NP as animate or inanimate are scarce in the surrounding textual material. In English anaphora resolution, recognition of the animacy of NPs improves the accuracy with which gender agreement restrictions can be enforced between pronouns and candidates.
In this work, the animacy of English NPs is identified using a combination of a number of tactics. The main one is the use of WordNet. Three noun hierarchies were identified as being indicative of animate entities. The remaining hierarchies are taken to indicate nouns referring to inanimate entities. Four hierarchies of verb senses were identified as containing verbs expected to require an animate subject. By examining the distribution of textual head nouns and main verbs in WordNet, the animacy of the NP or subject NP is assessed. A number of heuristics are used to reinforce or undermine the system’s confidence as to the animacy of a NP. The new system is incorporated into an existing pronominal anaphora resolution system and tested on a text with a high proportion of gender-marked pronouns. The performance of the system using the new method for animate entity recognition is compared with that of the original.