Computational Pragmatics

by

Harry Bunt

• LAST REVIEWED: 29 July 2020
• LAST MODIFIED: 29 July 2020
• DOI: 10.1093/obo/9780199772810-0264

Introduction

Pragmatics as a branch of linguistics can be characterized as the study of the relations between linguistic properties of utterances on the one hand, and aspects of the context in which a given utterance is used on the other. Computational pragmatics is pragmatics with computational means, which include models of dialogue management processes, collections of language use data, annotation schemes and standards, software tools for corpus creation, annotation and exploration, process models of language generation and interpretation, context representations, and inference methods for context-dependent utterance generation and interpretation processes. The linguistic side of the relations that are studied in pragmatics is formed primarily by utterances in a conversation or sentences in a written text. In the case of written text the context side consists of the surrounding text and the setting in which the text is meant to function. In spoken or multimodal dialogue, the context of an utterance is formed by what has been said before and the interactive setting, but additionally by other perceptual, social, and mutual epistemic information (see Context Modeling). Much of this information is dynamic, as it changes during a dialogue and, more importantly, as a result of the dialogue, since the participants in a conversation influence each other’s state of information when they understand each other. Dialogue contexts are thus updated continuously as an effect of communication. Central to computational pragmatics is the development and use of computational tools and models for studying the relations between utterances and their context of use. Essential for understanding these relations are the use of inference and the description of language in terms of actions that are inspired by the context and that are intended to change the context. This bibliography therefore focuses on publications concerned with the computational modeling of dialogue in terms of communicative actions including the use of inference for utterance interpretation. It also considers the more static analysis of discourse coherence and semantic relations in text, and concludes with references to recent activities concerning the construction and use of resources in computational pragmatics, in particular annotation schemes, annotated corpora, and tools for corpus construction and use. The popularity of probabilistic approaches to natural language processing can also be seen in studies of pragmatic aspects of language use, although these approaches are so far not as important as in some other areas of language processing. The so-called rational speech acts (RSA) model treats language use as a recursive process in which probabilistic speaker and listener agents reason about each other’s intentions to enrich the literal semantics of their language along broadly Gricean lines. The core references for this approach are also included in this biography under Inference in Language Processing.

General Introductions

Computational pragmatics is a young branch of computational linguistics, for which no specialized textbooks or general overview works exist. Allen 1995 and Jurafsky and Martin 2009 are general textbooks on computational linguistics that include chapters on computational pragmatics. Bunt and Black 2000 is the first published introduction to computational pragmatics, with a focus on abductive inference and dialogue modeling. Bunt 2015 is a more recent overview of research issues and activities in computational pragmatics. Scontras, et al. 2017 is an online course book that introduces the Rational Speech Act model.

• Allen, James. 1995. Natural language understanding. 2d ed. Redwood City, CA: Benjamin/Cummings.

  For many years Allen’s book was the key textbook in computational linguistics, covering the areas of syntax, semantics, and pragmatics in detail, but it has not been kept up to date with developments in statistical language processing.

• Bunt, Harry. 2015. Computational pragmatics. In Oxford handbook of pragmatics. Edited by Yan Huang, 326–345. New York: Oxford Univ. Press.

  Recent brief overview of issues and research in computational pragmatics, with a focus on computational dialogue modeling, corpora, annotation, and software tools.

• Bunt, Harry, and William Black. 2000. The ABC of computational pragmatics. In Abduction, belief and context in dialogue: Studies in computational pragmatics. Edited by Harry Bunt and William Black, 1–46. Amsterdam: Benjamins.

  General introduction to the field of computational pragmatics, with a focus on ‘pragmatic’ inference in language processing (in particular on abduction) and computational dialogue modeling.

• Jurafsky, Daniel, and James H. Martin. 2009. Speech and language processing: An introduction to natural language processing, speech recognition, and computational linguistics. 2d ed. Upper Saddle River, NJ: Pearson Prentice Hall.

  Jurafsky’s and Martin’s book is today the key textbook in computational linguistics, with substantial material on all three areas of syntax, semantics, and pragmatics, including material on statistical processing. The online 3rd edition draft from September 2018 includes two chapters on dialogue systems.

• Scontras, Gregory, Michael Tessler, and Michael Franke. 2017. Probabilistic language understanding: An introduction to the Rational Speech Act framework.

  Online course book that serves as a practical introduction to the Rational Speech Act (RSA) model.