Learning to Model Multilingual Unrestricted Coreference in OntoNotes
Baoli Li · 2012
Coreference resolution, which aims at correctly linking meaningful expressions in text, is a much challenging problem in Natural Language Processing community. This paper describes the multilingual coreference modeling system of Web Information Processing Group, Henan University of Technology, China, for the CoNLL-2012 shared task (closed track). The system takes a supervised learning strategy, and consists of two cascaded components: one for detecting mentions, and the other for clustering mentions. To make the system applicable for multiple languages, generic syntactic and semantic features are used to model coreference in text. The system obtained combined official score 41.88 over three languages (Arabic, Chinese, and English) and ranked 7 th among the 15 systems in the closed track. 1