Coreference resolution aims at resolving repeated references to an object in a document
and forms a core component of natural language processing (NLP) research. When used as …

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

The CoNLL-2012 shared task involved predicting coreference in English, Chinese, and
Arabic, using the final version, v5. 0, of the OntoNotes corpus. It was a follow-on to the …

Classical coreference systems encode various syntactic, discourse, and semantic
phenomena explicitly, using heterogenous features computed from hand-crafted heuristics …

We examine the task of resolving complex cases of definite pronouns, specifically those for
which traditional linguistic constraints on coreference (eg, Binding Constraints, gender and …

With rise of digital age, there is an explosion of information in the form of news, articles,
social media, and so on. Much of this data lies in unstructured form and manually managing …

Discourse Processing here is framed as marking up a text with structural descriptions on
several levels, which can serve to support many language-processing or text-mining tasks …

Automatically extracting information from unstructured text in pharmaceutical documents is
important for drug discovery and development. This information can be integrated with …

We present a new release of the Czech-English parallel corpus CzEng. CzEng 1.6 consists
of about 0.5 billion words (“gigaword”) in each language. The corpus is equipped with …

This paper presents the second release of arrau, a multigenre corpus of anaphoric
information created over 10 years to provide data for the next generation of …