Traditional approaches to the task of ACE event extraction primarily rely on elaborately
designed features and complicated natural language processing (NLP) tools. These …

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 …

Traditional approaches to the task of ACE event extraction usually rely on sequential
pipelines with multiple stages, which suffer from error propagation since event triggers and …

Event detection remains a challenge because of the difficulty of encoding the word
semantics in various contexts. Previous approaches have heavily depended on language …

Most previous event extraction studies have relied heavily on features derived from
annotated event mentions, thus cannot be applied to new event types without annotation …

With the rapid development of information technology, online platforms have produced
enormous text resources. As a particular form of Information Extraction (IE), Event Extraction …

We propose a brand new “Liberal” Event Extraction paradigm to extract events and discover
event schemas from any input corpus simultaneously. We incorporate symbolic (eg, Abstract …

Chinese event extraction is a challenging task in information extraction. Previous
approaches highly depend on sophisticated feature engineering and complicated natural …

Neural network based models commonly regard event detection as a word-wise
classification task, which suffer from the mismatch problem between words and event …

The identification of complex semantic structures such as events and entity relations, already
a challenging Information Extraction task, is doubly difficult from sources written in under …