A micro-topic model for coreference resolution based on theme-rheme structure

Abstract

Coreference resolution is a major task of natural language processing. Although the mention-pair model is one of the most influential learning-based coreference models, it is hard to make any further improvements of the performance because of its inherent defects. From the perspective of discourse analysis, a micro-topic model based on the theme-rheme structure is proposed for coreference resolution in this paper. Compared with the traditional mention object recognition in text space, this model reduces problem space and complexity. The effectiveness of this model was evaluated by preliminary experimental in CoNLL-2012 shared task datasets and discourse topic corpus (DTC) tagged by us.