Temporal and Aspectual Entailment

Thomas Kober, Sander Bijl de Vroe, Mark Steedman

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Inferences regarding Jane’s arrival in London from predications such as Jane is going to Londonor Jane has gone to London depend on tense and aspect of the predications. Tense determines the temporal location of the predication in the past, present or future of the time of utterance. The aspectual auxiliaries on the other hand specify the internal constituency of the event, i.e. whether the event of going to London is completed and whether its consequences hold at that time or not. While tense and aspect are among the most important factors for determining natural language inference, there has been very little work to show whether modern NLP models capture these semantic concepts. In this paper we propose a novel entailment dataset and analyse the ability of a range of recently proposed NLP models to perform inference on temporal predications. We show that the models encode a substantial amount of morphosyntactic information relating to tense and aspect, but fail to model inferences that require reasoning with these semantic properties.
Original languageEnglish
Title of host publicationProceedings of the 13th International Conference on Computational Semantics - Long Papers
Place of PublicationGothenburg, Sweden
PublisherAssociation for Computational Linguistics
Number of pages17
Publication statusPublished - 23 May 2019
Event13th International Conference on Computational Semantics - Gothenburg, Sweden
Duration: 23 May 201927 May 2019


Conference13th International Conference on Computational Semantics
Abbreviated titleIWCS 2019
Internet address


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