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An Analysis of Language Frequency and Error Correction for Esperanto

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Computer Science > Computation and Language

arXiv:2402.09696 (cs)
[Submitted on 15 Feb 2024 (v1), last revised 17 Aug 2026 (this version, v3)]

Title:An Analysis of Language Frequency and Error Correction for Esperanto

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Abstract:Current Grammar Error Correction (GEC) initiatives tend to focus on major languages, with less attention given to low-resource languages like Esperanto. In this article, we begin to bridge this gap by first conducting a comprehensive frequency analysis using the Eo-GP dataset, created explicitly for this purpose. We then introduce the Eo-GEC dataset, derived from authentic user cases and annotated with fine-grained linguistic details for error identification. Leveraging GPT-3.5 and GPT-4, our experiments show that GPT-4 outperforms GPT-3.5 in both automated and human evaluations, highlighting its efficacy in addressing Esperanto's grammatical peculiarities and illustrating the potential of advanced language models to enhance GEC strategies for less commonly studied languages.
Comments: Data is now available at: this https URL
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2402.09696 [cs.CL]
  (or arXiv:2402.09696v3 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2402.09696
arXiv-issued DOI via DataCite

Submission history

From: Junhong Liang [view email]
[v1] Thu, 15 Feb 2024 04:10:25 UTC (1,847 KB)
[v2] Fri, 16 Feb 2024 02:19:49 UTC (1,847 KB)
[v3] Mon, 17 Aug 2026 22:27:25 UTC (1,843 KB)
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