mlsanityData to 7 Oct 2026

Linguistic ambiguity analysis in ChatGPT

arXiv 2302.06426 ↗First posted 13 Feb 2023cs.CL cs.AIcited by 14

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Abstract (arXiv)

Linguistic ambiguity is and has always been one of the main challenges in Natural Language Processing (NLP) systems. Modern Transformer architectures like BERT, T5 or more recently InstructGPT have achieved some impressive improvements in many NLP fields, but there is still plenty of work to do. Motivated by the uproar caused by ChatGPT, in this paper we provide an introduction to linguistic ambiguity, its varieties and their relevance in modern NLP, and perform an extensive empiric analysis. ChatGPT strengths and weaknesses are revealed, as well as strategies to get the most of this model.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 8 of its 30 references that are in the map. First posted on arXiv 13 Feb 2023.

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8 of 30 references.

References · 8

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
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  3. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  4. 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,970
  5. 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 8; 2024: 1; 2025: 1; 2026: 4.

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  1. 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Modelscited by 152
  2. 2023Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulnesscited by 130
  3. 2023A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasetscited by 123
  4. 2023Decoding ChatGPT: A Taxonomy of Existing Research, Current Challenges, and Possible Future Directionscited by 18
  5. 2023Playing with words: Comparing the vocabulary and lexical diversity of ChatGPT and humanscited by 8
  6. 2023Public Perceptions of Gender Bias in Large Language Models: Cases of ChatGPT and Erniecited by 8
  7. 2023Humans are Still Better than ChatGPT: Case of the IEEEXtreme Competitioncited by 5
  8. 2024Grammaticality Representation in ChatGPT as Compared to Linguists and Laypeoplecited by 5
  9. 2023Gender Bias in Transformer Models: A comprehensive surveycited by 2
  10. 2025Generative AI and the future of scientometrics: current topics and future questionscited by 1
  11. 2026Evaluating ChatGPT on Medical Information Extraction Tasks: Performance, Explainability and Beyondcited by 1
  12. 2026An Exploration-Analysis-Disambiguation Reasoning Framework for Word Sense Disambiguation with Low-Parameter LLMscited by 1
2 more
  1. 2026Evaluating Chinese Ambiguity Understanding in Large Language Modelscited by 0
  2. 2026When a Name Is Not a Name: A Benchmark Dataset and Distilled Reasoning for Culturally Entangled Bangla Homographs in Low-Resource LLMscited by 0