A Kind Introduction to Lexical and Grammatical Aspect, with a Survey of Computational Approaches

TL;DR

This paper surveys computational methods for modeling lexical and grammatical aspect, emphasizing its importance in understanding the temporal structure of situations for advancing NLP language understanding.

Contribution

It provides an overview of linguistic concepts and reviews computational approaches to aspect, highlighting the need for systematic handling in NLP.

Findings

Highlights the importance of aspect in semantic modeling

Reviews key linguistic concepts like telicity and stativity

Argues for systematic aspect handling in future NLP

Abstract

Aspectual meaning refers to how the internal temporal structure of situations is presented. This includes whether a situation is described as a state or as an event, whether the situation is finished or ongoing, and whether it is viewed as a whole or with a focus on a particular phase. This survey gives an overview of computational approaches to modeling lexical and grammatical aspect along with intuitive explanations of the necessary linguistic concepts and terminology. In particular, we describe the concepts of stativity, telicity, habituality, perfective and imperfective, as well as influential inventories of eventuality and situation types. We argue that because aspect is a crucial component of semantics, especially when it comes to reporting the temporal structure of situations in a precise way, future NLP approaches need to be able to handle and evaluate it systematically in order to achieve human-level language understanding.