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

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 …

We use machine learning techniques to find the best combination of local focus and lexical
distance features for identifying the anchor of mereological bridging references. We find that …

Traditional learning-based coreference resolvers operate by training the mention-pair model
for determining whether two mentions are coreferent or not. Though conceptually simple and …

Research on coreference resolution and summarization has modeled the way entities are
realized as concrete phrases in discourse. In particular there exist models of the noun …

We compare two ways of obtaining lexical knowledge for antecedent selection in other-
anaphora and definite noun phrase coreference. Specifically, we compare an algorithm that …

This thesis presents a study of anaphora in biomedical scientific literature and focuses on
tackling the problem of anaphora resolution in this domain. Biomedical literature has been …

Identifying given and new information within a text has long been addressed as a research
issue. However, there has previously been no accurate computational method for assessing …

L'évaluation et l'entraînement d'algorithmes pour le traitement automatique d'anaphores
nécessitent le développement de corpus annotés. Dans cet article, nous proposons une …

We present a model for automatically predicting information status labels for German
referring expressions. We train a CRF on manually annotated phrases, and predict a fine …