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Logic Journal of IGPL 2003 11(4):457-484; doi:10.1093/jigpal/11.4.457
© 2003 by Oxford University Press
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Original Article

A Computational Framework For Understanding Mathematical Discoursexy

Claus Zinn

Division of Informatics, University of Edinburgh, 2 Buccleuch Place, Edinburgh, EH8 9LW, Scotland, UK. E-mail: zinn{at}inf.ed.ac.uk

An essential part of text understanding is to make explicit the implicit parts of discourse, namely its presuppositions and implications. For mathematical discourse, the explicitly stated portions of a text do not make sense taken in the absence of the illuminating implicit content. A reader, human or machine, must be able to "read between the lines".

In this paper, we present a computational framework for understanding informal mathematical discourse, extending and integrating state-of-the-art technologies from natural language processing (discourse representation theory) and automated reasoning (proof planning) in a novel and promising way. For representing mathematical discourse, we introduce proof representation structures (PRSs) as the central data structure. PRSs are a considerable extension to discourse representation structures accommodating our need for representing discourse structure, and handling substructures and mathematical sentences as first-class citizens. For constructing PRSs, we propose a discourse update algorithm that is powered by pragmatics. It incorporates an underspecified semantic representation into the proof context by making use of mathematical and meta-mathematical knowledge, employing a proof planner. Proof plans, capturing common patterns of reasoning in mathematical proofs, enable us to gain a high level discourse understanding, allowing us to follow the proof author's main line of argument. Given such high-level discourse understanding, we can then compute the parts "between the lines", those pieces of information that the proof author has taken for granted. We demonstrate that much inference is required to compute this implicit information.

Key Words: Text Understanding, Proof Verification, Discourse Representation Theory, Proof Planning


Revised 15 September 2002.


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