The advancements of sensing technologies, including remote sensing, in situ sensing,
social sensing, and health sensing, have tremendously improved our capability to observe …

Abstract Information systems need to process a large amount of event monitoring data. The
process of finding the relationships between events is called correlation, which creates a …

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 …

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 …

Event extraction, which aims to identify event triggers of pre-defined event types and their
arguments of specific roles, is a challenging task in NLP. Most traditional approaches …

Numerous important events happen everyday and everywhere but are reported in different
media sources with different narrative styles. How to detect whether real-world events have …

Event detection (ED), which means identifying event trigger words and classifying event
types, is the first and most fundamental step for extracting event knowledge from plain text …

Event extraction has long been a challenging task, addressed mostly with supervised
methods that require expensive annotation and are not extensible to new event ontologies …