How many words does ChatGPT know? The answer is ChatWords
Not on the map. Why?
Abstract (arXiv)
The introduction of ChatGPT has put Artificial Intelligence (AI) Natural Language Processing (NLP) in the spotlight. ChatGPT adoption has been exponential with millions of users experimenting with it in a myriad of tasks and application domains with impressive results. However, ChatGPT has limitations and suffers hallucinations, for example producing answers that look plausible but they are completely wrong. Evaluating the performance of ChatGPT and similar AI tools is a complex issue that is being explored from different perspectives. In this work, we contribute to those efforts with ChatWords, an automated test system, to evaluate ChatGPT knowledge of an arbitrary set of words. ChatWords is designed to be extensible, easy to use, and adaptable to evaluate also other NLP AI tools. ChatWords is publicly available and its main goal is to facilitate research on the lexical knowledge of AI tools. The benefits of ChatWords are illustrated with two case studies: evaluating the knowledge that ChatGPT has of the Spanish lexicon (taken from the official dictionary of the "Real Academia Espa~nola") and of the words that appear in the Quixote, the well-known novel written by Miguel de Cervantes. The results show that ChatGPT is only able to recognize approximately 80% of the words in the dictionary and 90% of the words in the Quixote, in some cases with an incorrect meaning. The implications of the lexical knowledge of NLP AI tools and potential applications of ChatWords are also discussed providing directions for further work on the study of the lexical knowledge of AI tools.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 12 of its 39 references that are in the map. First posted on arXiv 28 Sep 2023.
Builds on
12 of 39 references.
References · 12
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Built on by
Citing papers per year: 2023: 1; 2024: 4; 2025: 0; 2026: 1.
6 papers.
- 2024NewTerm: Benchmarking Real-Time New Terms for Large Language Models with Annual Updatescited by 8
- 2024Using large language models to estimate features of multi-word expressions: Concreteness, valence, arousalcited by 4
- 2024The #Somos600M Project: Generating NLP resources that represent the diversity of the languages from LATAM, the Caribbean, and Spaincited by 2
- 2023Establishing Vocabulary Tests as a Benchmark for Evaluating Large Language Modelscited by 1
- 2024Open Conversational LLMs do not know most Spanish wordscited by 1
- 2026AI-Assisted Requirements Engineering: An Empirical Evaluation Relative to Expert Judgmentcited by 0
- 2026AI-Assisted Requirements Engineering: An Empirical Evaluation Relative to Expert Judgment16 Apr 2026
- 2024NewTerm: Benchmarking Real-Time New Terms for Large Language Models with Annual Updates28 Oct 2024
- 2024Using large language models to estimate features of multi-word expressions: Concreteness, valence, arousal16 Aug 2024
- 2024The #Somos600M Project: Generating NLP resources that represent the diversity of the languages from LATAM, the Caribbean, and Spain1 Jul 2024
- 2024Open Conversational LLMs do not know most Spanish words21 Mar 2024
- 2023Establishing Vocabulary Tests as a Benchmark for Evaluating Large Language Models23 Oct 2023