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A Survey and Classification of Controlled Natural Languages

arXiv 1507.01701 ↗First posted 7 Jul 2015cs.CLcited by 18

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Abstract (arXiv)

What is here called controlled natural language (CNL) has traditionally been given many different names. Especially during the last four decades, a wide variety of such languages have been designed. They are applied to improve communication among humans, to improve translation, or to provide natural and intuitive representations for formal notations. Despite the apparent differences, it seems sensible to put all these languages under the same umbrella. To bring order to the variety of languages, a general classification scheme is presented here. A comprehensive survey of existing English-based CNLs is given, listing and describing 100 languages from 1930 until today. Classification of these languages reveals that they form a single scattered cloud filling the conceptual space between natural languages such as English on the one end and formal languages such as propositional logic on the other. The goal of this article is to provide a common terminology and a common model for CNL, to contribute to the understanding of their general nature, to provide a starting point for researchers interested in the area, and to help developers to make design decisions.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Jul 2015.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 0; 2023: 4; 2024: 3; 2025: 3; 2026: 6.

18 papers.

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  1. 2023A Comprehensive Survey on Applications of Transformers for Deep Learning Taskscited by 70
  2. 2024LLASP: Fine-tuning Large Language Models for Answer Set Programmingcited by 8
  3. 2025Towards Formal Verification of LLM-Generated Code from Natural Language Promptscited by 8
  4. 2024Towards Automatic Composition of ASP Programs from Natural Language Specificationscited by 7
  5. 2023CNL2ASP: converting controlled natural language sentences into ASPcited by 5
  6. 2026OntoLearner: A Modular Python Library for Ontology Learning with Large Language Modelscited by 3
  7. 2024SpeciaLex: A Benchmark for In-Context Specialized Lexicon Learningcited by 2
  8. 2021Understanding Pre-Editing for Black-Box Neural Machine Translationcited by 1
  9. 2023HyperPIE: Hyperparameter Information Extraction from Scientific Publicationscited by 1
  10. 2021An NLG pipeline for a legal expert system: a work in progresscited by 0
  11. 2023Trustworthy Formal Natural Language Specificationscited by 0
  12. 2025Natural Language Generationcited by 0
6 more
  1. 2025When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs'' for Human-AI Interactioncited by 0
  2. 2026Bridging Pedagogy and Play: Introducing a Language Mapping Interface for Human-AI Co-Creation in Educational Game Designcited by 0
  3. 2026Open Machine Translation for Esperantocited by 0
  4. 2026BLAST: Benchmarking LLMs with ASP-based Structured Testingcited by 0
  5. 2026Ceci n'est pas une pipe: AI systems as semantic abstractionscited by 0
  6. 2026Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcriptscited by 0