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 …

Statistical significance testing is a standard statistical tool designed to ensure that
experimental results are not coincidental. In this opinion/theoretical paper we discuss the …

Recent years have seen a gradual shift of focus from entity-based tasks to event-based tasks
in information extraction research. Being a core event-based task, event coreference …

Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are
also an essential kind of knowledge in the world, which trigger the spring up of event-centric …

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

The diverse relationships among real-world events, including coreference, temporal, causal,
and subevent relations, are fundamental to understanding natural languages. However, two …

There have been a wide range of recent annotated corpora concerning events, either
regarding event coreference, the temporal order of events, hierarchical “subevent” structure …

Most successful information extraction systems operate with access to a large collection of
documents. In this work, we explore the task of acquiring and incorporating external …

Recognizing coreferring events and entities across multiple texts is crucial for many NLP
applications. Despite the task's importance, research focus was given mostly to within …

In this paper we examine the representativeness of the EventCorefBank (ECB)(Bejan and
Harabagiu, 2010) with regards to the language population of large-volume streams of news …