Abstract Entity Coreference Resolution is the task of resolving all mentions in a document
that refer to the same real world entity and is considered as one of the most difficult tasks in …

We study a new problem of cross-lingual transfer learning for event coreference resolution
(ECR) where models trained on data from a source language are adapted for evaluations in …

In this paper, we present coreference resolution experiments with a newly created
multilingual corpus CorefUD. We focus on the following languages: Czech, Russian, Polish …

It is increasingly common to evaluate the same coreference resolution (CR) model on
multiple datasets. Do these multi-dataset evaluations allow us to draw meaningful …

Coreference resolution models are often evaluated on multiple datasets. Datasets vary,
however, in how coreference is realized--ie, how the theoretical concept of coreference is …

Complex Word Identification (CWI) is a task centered on detecting hard-to-understand
words, or groups of words, in texts from different areas of expertise. The purpose of CWI is to …

Coreference resolution systems aim to recognize and cluster together mentions of the same
underlying entity. While there exist large amounts of research on broadly spoken languages …

Multilingual coreference resolution (MCR) has been a long-standing and challenging task.
With the newly proposed multilingual coreference dataset, CorefUD (Nedoluzhko et al …

Mention detection is an important component of the Coreference Resolution (CR) system,
where mentions such as name, nominal, and pronominals are identified. These mentions …

Coreference resolution, the task of identifying expressions in text that refer to the same
entity, is a critical component in various natural language processing (NLP) applications …