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 …

Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are
also an essential kind of knowledge in the world, which trigger the spring up of event-centric …

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 …

Traditional knowledge graph embedding (KGE) aims to map entities and relations into
continuous space vectors to provide high-quality data feature representation for downstream …

Knowledge graphs (KGs) represent entities and relations as computable networks, which is
of great value for discovering hidden knowledge and patterns. Geographic KGs mainly …

Event extraction aims to identify an event and then extract the arguments participating in the
event. Despite the great success in sentencelevel event extraction, events are more …

Conceptualization, or viewing entities and situations as instances of abstract concepts in
mind and making inferences based on that, is a vital component in human intelligence for …

Semantic information in judgement documents has been an important source in Artificial
Intelligence and Law. Sequential representation is the traditional structure for analyzing …

As the main channel for people to obtain information and express their opinions, online
media generate a huge amount of unstructured news documents every day and make it …

Incorporating external knowledge into dialogue generation has been proven to benefit the
performance of an open-domain Dialogue System (DS), such as generating informative or …