As user demands become increasingly sophisticated, search engines today are competing in more than just returning document results from the Web. One area of competition is providi...
A large body of prior research on coreference resolution recasts the problem as a two-class classification problem. However, standard supervised machine learning algorithms that m...
This paper describes the participation of RelaxCor in the Semeval-2010 task number 1: "Coreference Resolution in Multiple Languages". RelaxCor is a constraint-based grap...
We aim to shed light on the state-of-the-art in NP coreference resolution by teasing apart the differences in the MUC and ACE task definitions, the assumptions made in evaluation ...
Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
Despite the existence of several noun phrase coreference resolution data sets as well as several formal evaluations on the task, it remains frustratingly difficult to compare resu...
This paper explores the effect that different corpus configurations have on the performance of a coreference resolution system, as measured by MUC, B3, and CEAF. By varying separa...
We present a supervised learning approach to identification of anaphoric and non-anaphoric noun phrases and show how such information can be incorporated into a coreference resolu...
In this paper we present a new, multilingual data-driven method for coreference resolution as implemented in the SWIZZLE system. The results obtained after training this system on...
This paper proposes a new approach for coreference resolution which uses the Bell tree to represent the search space and casts the coreference resolution problem as finding the be...
Xiaoqiang Luo, Abraham Ittycheriah, Hongyan Jing, ...