CoNLL 2012 Shared Task

We in this paper present the model for our participation (BCMI) in the CoNLL-2012 Shared Task. This paper describes a pure rule-based method, which assembles dif- ferent filters in a …...

We describe our system for the CoNLL-2012 shared task, which seeks to model corefer- ence in OntoNotes for English, Chinese, and Arabic. We adopt a hybrid approach to coreference resolution, …...

We describe a machine learning system based on large margin structure perceptron for unre- stricted coreference resolution that introduces two key modeling techniques: latent corefer- ence trees and entropy guided …...

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 …...

The current work presents the participa- tion of UBIU (Zhekova and K¨ubler, 2010) in the CoNLL-2012 Shared Task: Model- ing Multilingual Unrestricted Coreference in OntoNotes (Pradhan et al., 2012). Our …...

Coreference resolution plays a critical role in discourse analysis. This paper focuses on exploiting zero pronouns to improve Chi- nese coreference resolution. In particular, a simplified semantic role labeling framework …...

Learning a hierarchy of specialized pairwise models for coreference resolution This paper proposes a new method for significantly improving the performance of pairwise coreference models. Given a set of indicators, …...

Coreference resolution systems are typically trained with heuristic loss functions that re- quire careful tuning. In this paper we in- stead apply reinforcement learning to directly optimize a neural mention-ranking …...