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

TL;DR

This paper introduces Codeco, a new grammar notation tailored for controlled natural languages and predictive editors, enabling effective lookahead and handling complex structures like anaphora, demonstrated with ACE.

Contribution

The paper presents Codeco, a novel grammar formalism and parsing algorithm designed for CNLs and predictive editors, addressing limitations of existing frameworks.

Findings

Codeco effectively models ACE in a predictive editor context.

The extended chart parsing algorithm is practical and efficient.

The approach supports complex nonlocal structures like anaphora.

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 (ACE) has been represented in Codeco. Evaluation of this grammar and the parser implementation shows that the approach is practical, adequate and efficient.