Tense and Aspect Semantics for Sentential AMR
Lucia E. Donatelli, Nathan Schneider, William Croft, Michael Regan · ScholarWorks@UMassAmherst (University of Massachusetts Amherst) · 2019
Many English tense and aspect semantic contrasts are not currently captured within Abstract Meaning Representation (AMR) annotations.The proposed framework augments the representation of finite predications in AMR to include a four-way temporal distinction (event time before, up to, at, or after speech time) and several aspectual distinctions (including static vs. dynamic, habitual vs. episodic, and telic vs. atelic).We validate this approach with a small annotation study of sentences from The Little Prince and report details of ongoing discussion to refine the framework.This will enable AMR to be used for NLP tasks and applications that require sophisticated reasoning about time and event structure.