March 20, 2024, 4:48 a.m. | Haochen Li, Di Geng

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.12523v1 Announce Type: new
Abstract: Events describe the state changes of entities. In a document, multiple events are connected by various relations (e.g., Coreference, Temporal, Causal, and Subevent). Therefore, obtaining the connections between events through Event-Event Relation Extraction (ERE) is critical to understand natural language. There are two main problems in the current ERE works: a. Only embeddings of the event triggers are used for event feature representation, ignoring event arguments (e.g., time, place, person, etc.) and their structure within …

abstract arxiv causal cs.ai cs.cl document embeddings event events extraction graph language multiple natural natural language relations state temporal through type via

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Machine Learning Research Scientist

@ d-Matrix | San Diego, Ca