TL;DR
Embedded controlled natural languages (CNLs) are specialized language fragments with parsers recognizing full host languages, enabling better processing and user feedback, exemplified through GF implementation and applications like machine translation.
Contribution
This paper introduces the concept of embedded CNLs, demonstrating their implementation in GF and their advantages over traditional CNLs in processing and feedback.
Findings
Embedded CNLs can recognize entire host languages.
GF effectively implements embedded CNLs.
Applications include improved machine translation feedback.
Abstract
Inspired by embedded programming languages, an embedded CNL (controlled natural language) is a proper fragment of an entire natural language (its host language), but it has a parser that recognizes the entire host language. This makes it possible to process out-of-CNL input and give useful feedback to users, instead of just reporting syntax errors. This extended abstract explains the main concepts of embedded CNL implementation in GF (Grammatical Framework), with examples from machine translation and some other ongoing work.
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Taxonomy
TopicsNatural Language Processing Techniques · Logic, programming, and type systems · AI-based Problem Solving and Planning