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Enriching Large-Scale Eventuality Knowledge Graph with Entailment Relations
[article]
2020
arXiv
pre-print
Computational and cognitive studies suggest that the abstraction of eventualities (activities, states, and events) is crucial for humans to understand daily eventualities. In this paper, we propose a scalable approach to model the entailment relations between eventualities ("eat an apple" entails "eat fruit"). As a result, we construct a large-scale eventuality entailment graph (EEG), which has 10 million eventuality nodes and 103 million entailment edges. Detailed experiments and analysis
arXiv:2006.11824v1
fatcat:2bgl2kjiejb2ldzljfr6ui4si4