Event Relation Extraction

8 papers with code • 0 benchmarks • 0 datasets

To extract relations among events, such as event coreference, temporal, causal and subevent relations.

Most implemented papers

From Discourse to Narrative: Knowledge Projection for Event Relation Extraction

TangJiaLong/Knowledge-Projection-for-ERE ACL 2021

Current event-centric knowledge graphs highly rely on explicit connectives to mine relations between events.

Selecting Optimal Context Sentences for Event-Event Relation Extraction

hieumdt/SCS-EERE AAAI 2022

To achieve this goal, our work addresses the problems of subevent relation extraction (SRE) and temporal event relation extraction (TRE) that aim to predict subevent and temporal relations between two given event mentions/triggers in texts.

MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction

thu-keg/maven-ere 14 Nov 2022

It contains 103, 193 event coreference chains, 1, 216, 217 temporal relations, 57, 992 causal relations, and 15, 841 subevent relations, which is larger than existing datasets of all the ERE tasks by at least an order of magnitude.

SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres

zjunlp/speech 23 May 2023

Event-centric structured prediction involves predicting structured outputs of events.

OmniEvent: A Comprehensive, Fair, and Easy-to-Use Toolkit for Event Understanding

thu-keg/omnievent 25 Sep 2023

Event understanding aims at understanding the content and relationship of events within texts, which covers multiple complicated information extraction tasks: event detection, event argument extraction, and event relation extraction.

Learning To Teach Large Language Models Logical Reasoning

chenmeiqii/teach-llm-lr 13 Oct 2023

Large language models (LLMs) have gained enormous attention from both academia and industry, due to their exceptional ability in language generation and extremely powerful generalization.

MAVEN-Arg: Completing the Puzzle of All-in-One Event Understanding Dataset with Event Argument Annotation

thu-keg/maven-argument 15 Nov 2023

Understanding events in texts is a core objective of natural language understanding, which requires detecting event occurrences, extracting event arguments, and analyzing inter-event relationships.