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Allen's Interval Algebra Makes the Difference

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arxiv 1909.01128 v1 pith:QM2NJNAG submitted 2019-09-03 cs.AI

classification cs.AI
keywords allenalgebraintervalcalculusdifferenceencodingentitiestemporal
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Allen's Interval Algebra constitutes a framework for reasoning about temporal information in a qualitative manner. In particular, it uses intervals, i.e., pairs of endpoints, on the timeline to represent entities corresponding to actions, events, or tasks, and binary relations such as precedes and overlaps to encode the possible configurations between those entities. Allen's calculus has found its way in many academic and industrial applications that involve, most commonly, planning and scheduling, temporal databases, and healthcare. In this paper, we present a novel encoding of Interval Algebra using answer-set programming (ASP) extended by difference constraints, i.e., the fragment abbreviated as ASP(DL), and demonstrate its performance via a preliminary experimental evaluation. Although our ASP encoding is presented in the case of Allen's calculus for the sake of clarity, we suggest that analogous encodings can be devised for other point-based calculi, too.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. ChronoSense: Exploring Temporal Understanding in Large Language Models with Time Intervals of Events

    cs.LG 2025-01 conditional novelty 6.0 of 10

    ChronoSense evaluates LLMs on all 13 Allen interval relations and temporal arithmetic, finding weak, inconsistent performance and signs of memorization across seven models.

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