Over the last several years, the field of natural language processing has been propelled
forward by an explosion in the use of deep learning models. This article provides a brief …

As a core task and an important link in the fields of natural language understanding and
information retrieval, information extraction (IE) can structure and semanticize unstructured …

Event extraction is challenging due to the complex structure of event records and the
semantic gap between text and event. Traditional methods usually extract event records by …

Event extraction (EE) is a crucial information extraction task that aims to extract event
information in texts. Previous methods for EE typically model it as a classification task, which …

The problem of event extraction requires detecting the event trigger and extracting its
corresponding arguments. Existing work in event argument extraction typically relies heavily …

Legal Artificial Intelligence (LegalAI) focuses on applying the technology of artificial
intelligence, especially natural language processing, to benefit tasks in the legal domain. In …

Event extraction requires high-quality expert human annotations, which are usually
expensive. Therefore, learning a data-efficient event extraction model that can be trained …

Traditional approaches to the task of ACE event extraction usually depend on manually
annotated data, which is often laborious to create and limited in size. Therefore, in addition …

Event extraction is of practical utility in natural language processing. In the real world, it is a
common phenomenon that multiple events existing in the same sentence, where extracting …

In this paper, we propose an effective yet efficient model PAIE for both sentence-level and
document-level Event Argument Extraction (EAE), which also generalizes well when there is …