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Context-Dependent Semantic Parsing for Temporal Relation Extraction
[article]
2021
arXiv
pre-print
Extracting temporal relations among events from unstructured text has extensive applications, such as temporal reasoning and question answering. While it is difficult, recent development of Neural-symbolic methods has shown promising results on solving similar tasks. Current temporal relation extraction methods usually suffer from limited expressivity and inconsistent relation inference. For example, in TimeML annotations, the concept of intersection is absent. Additionally, current methods do
arXiv:2112.00894v1
fatcat:6blsi6mduzeqpc5kbj7w4q4ice