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 …

Multiple entities in a document generally exhibit complex inter-sentence relations, and
cannot be well handled by existing relation extraction (RE) methods that typically focus on …

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 …

We present SENTiVENT, a corpus of fine-grained company-specific events in English
economic news articles. The domain of event processing is highly productive and various …

Event detection (ED) is a critical subtask of event extraction that seeks to identify event
triggers of certain types in texts. Despite significant advances in ED, existing methods …

Event detection systems rely on discrimination knowledge to distinguish ambiguous trigger
words and generalization knowledge to detect unseen/sparse trigger words. Current neural …

Event Detection (ED) is the task of identifying and classifying trigger words of event mentions
in text. Despite considerable research efforts in recent years for English text, the task of ED …

Event Extraction (EE) is one of the fundamental tasks in Information Extraction (IE) that aims
to recognize event mentions and their arguments (ie, participants) from text. Due to its …

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 …

Event processing is an active area of research in the Natural Language Processing
community, but resources and automatic systems developed so far have mainly addressed …