Temporal Relations Annotation and Extrapolation Based on Semi-intervals and Boundig Relations

Proceedings of the 28th International Conference on Computational Linguistics, pages 3313–3323 Barcelona, Spain (Online), December 8-13, 2020 3313 Temporal Relations Annotation and Extrapolation Based on Semi-intervals and Bounding Relations Alejandro Pimentel pimentel@comunidad.unam.mx Gemma Bel-Enguix gbele@iingen.unam.mx Universidad Nacional Aut´onoma de M´exico / M´exico Instituto de Ingenier´ıa / Ciudad de M´exico Gerardo Sierra gsierram@iingen.unam.mx Azucena Montes amr@cenidet.edu.mx Tecnol´ogico Nacional de M´exico / M´exico Centro Nacional de Investigaci´on y Desarrollo Tecnol´ogico / Cuernavaca Morelos Abstract The computational treatment of temporal relations is based on the work of Allen, who establishes 13 different types, and Freksa, who designs a cognitive procedure to manage them. Freksa’s notation is not widely used because, although it has cognitive and expressive advantages, it is too complex from the computational perspective. This paper proposes a system for the annotation and management of temporal relations that combines the richness and expressiveness of Freksa’s approach with the simplicity of Allen’s notation. Our method is summarized in the application of bounding relations, thanks to which it is possible to obtain the temporary representation of complete neighborhoods capable of representing vague temporal relations such as those that can be frequently found in a text. Such advantages are obtained without the need to greatly increase the complexity of the labeling process since the markup language is almost the same as TimeML, to which only a second temporary “relType” type label relationship is added. Our experiments show that the temporal relationships that present vagueness are in fact much more common than those in which a single relationship can be established precisely. For these reasons, our new labeling system achieves a more agreeable representation of temporal relations. 1 Introduction The understanding of the sequence in a narrative is a fundamental aspect in the comprehension of a text. News, novels, stories, narratives and many other types of texts contain events that occur in a certain chronological order, whether they express time explicitly or implicitly. The reader needs to obtain the temporal notion of the events that occur within a text in order to understand what is being narrated. There has been a large number of investigations, mainly theoretical, for the use of temporal relations to establish a chain of reference points, consisting mainly of events anchored to a known point in time or another event. With the help of these chains, timelines can be arranged. This type of approach allows for an abstract representation of time that is similar to the way in which humans communicate, since they rely on relative expressions, often using as reference the moment of speech or creation of the document. Temporal relations can be used similarly (Allen, 1983; Allen and Koomen, 1983; Vilain and Kautz, 1986; Freksa, 1992; Bramsen et al., 2006a; Bramsen et al., 2006b; Chambers et al., 2014). The identification of temporal relations between pairs of events or time intervals is a widely used way to express time. This type of annotation uses a set of realizations that has been designed as the core to classify and annotate each one …

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