Robust Pronominal Resolution within Chinese Text
鲁棒性的汉语人称代词消解

Anaphora Resolution is playing more and more important role in Natural Language Processing. There is an increasing need for the development of effective and robust strategies of anaphora resolution to meet the demands of practical applications. However, traditional approaches to anaphora resolution rely heavily on multilevel linguistic knowledge, such as syntactic, semantic, contextual and domain knowledge. It is undoubtedly difficult to acquire such knowledge at present. This paper presents a two-step approach with limited knowledge to resolve pronominal anaphora within Chinese text, which only uses number features, gender features and the features of grammatical roles. In this approach, a filter is firstly used to eliminate those expressions whose features are inconsistent with the pronoun, and thus form a set of potential antecedent candidates; then, a scoring algorithm is employed to calculate score of the candidates, and the candidate with the highest score is selected as the resultant antecedent. The algorithm does not examine each candidate in the set, but automatically determine whether to end the calculation or not by dynamically testing a termination condition, therefore the computational complexity is low. In addition, the approach does not need a deep analysis of the text, and can easily be implemented. Experiment shows the result is satisfactory.