The research focus of computational coreference resolution has exhibited a shift from
heuristic approaches to machine learning approaches in the past decade. This paper …

Coreference resolution is the task of determining linguistic expressions that refer to the same
real-world entity in natural language. Research on coreference resolution in the general …

We propose a new deterministic approach to coreference resolution that combines the
global information and precise features of modern machine-learning models with the …

Traditional learning-based coreference resolvers operate by training a mentionpair classifier
for determining whether two mentions are coreferent or not. Two independent lines of recent …

Web-scale data has been used in a diverse range of language research. Most of this
research has used web counts for only short, fixed spans of context. We present a unified …

The main contributions of this thesis are as follows: 1. We introduce a general model for
coreference and explore its application to German.• The model features an incremental …

Anaphora resolution (coreference) systems designed for the CONLL 2012 dataset typically
cannot handle key aspects of the full anaphora resolution task such as the identification of …

A discourse typically involves numerous entities, but few are mentioned more than once.
Distinguishing those that die out after just one mention (singleton) from those that lead …

Abstract We present Nada: the Non-A naphoric D etection A lgorithm. Nada is a novel,
publicly-available program that accurately distinguishes between the referential and non …

Recent work has shown that explicitly identifying and filtering non-anaphoric mentions prior
to coreference resolution can improve the performance of a coreference system. We present …