The task of resolving repeated objects in natural languages is known as coreference
resolution, and it is an important part of modern natural language processing. It is classified …

Event extraction (EE) is a crucial research task for promptly apprehending event information
from massive textual data. With the rapid development of deep learning, EE based on deep …

Event is a common but non-negligible knowledge type. How to identify events from texts,
extract their arguments, even analyze the relations between different events are important …

Information extraction is the process of converting unstructured text into a structured data
base containing selected information from the text. It is an essential step in making the …

The task of event relation extraction (ERE) aims to organize multiple events and their
relations as a directed graph. However, existing ERE methods exhibit two limitations:(1) …

An important problem of Information Extraction involves Event Causality Identification (ECI)
that seeks to identify causal relation between pairs of event mentions. Prior models for ECI …

We present a new information extraction system that can automatically construct temporal
event graphs from a collection of news documents from multiple sources, multiple languages …

We study the problem of event coreference resolution (ECR) that seeks to group coreferent
event mentions into the same clusters. Deep learning methods have recently been applied …

Cross-document event coreference resolution (CD-ECR) is a task of clustering event
mentions across multiple documents that refer to the same real-world events. Previous …

Event coreference resolution is an important research problem with many applications.
Despite the recent remarkable success of pretrained language models, we argue that it is …