A Principled Approach to Grammars for Controlled Natural Languages and Predictive Editors

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Controlled natural languages (CNL) with a direct mapping to formal logic have been proposed to improve the usability of knowledge representation systems, query interfaces, and formal specifications. Predictive editors are a popular approach to solve the problem that CNLs are easy to read but hard to write. Such predictive editors need to be able to "look ahead" in order to show all possible continuations of a given unfinished sentence. Such lookahead features, however, are difficult to implement in a satisfying way with existing grammar frameworks, especially if the CNL supports complex nonlocal structures such as anaphoric references. Here, methods and algorithms are presented for a new grammar notation called Codeco, which is specifically designed for controlled natural languages and predictive editors. A parsing approach for Codeco based on an extended chart parsing algorithm is presented. A large subset of Attempto Controlled English has been represented in Codeco. Evaluation of this grammar and the parser implementation shows that the approach is practical, adequate and efficient.

Original languageEnglish
Pages (from-to)33-70
Number of pages38
JournalJournal of Logic, Language and Information
Volume22
Issue number1
DOIs
Publication statusPublished - 2013
Externally publishedYes

Fingerprint

grammar
editor
Formal logic
Knowledge representation
language
Set theory
formal logic
evaluation
Grammar
Controlled
Natural Language
Formal specification
Parsing

Keywords

  • Anaphoric references
  • Attempto Controlled English
  • Chart parsing
  • Controlled natural languages
  • Predictive editors

Cite this

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A Principled Approach to Grammars for Controlled Natural Languages and Predictive Editors. / Kuhn, Tobias.

In: Journal of Logic, Language and Information, Vol. 22, No. 1, 2013, p. 33-70.

Research output: Contribution to JournalArticleAcademicpeer-review

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