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AI Corpus Linguist: More than a Year of Experience

Summary

Querying language corpora usually requires a formal query language such as CQL, which most humanities scholars never learn. The authors built Corpus Linguist, a custom GPT on OpenAI's platform that lets users ask research questions in plain language. The system is connected to multilingual corpora through the Czech National Corpus (CNC) API. Its hybrid design works in stages. The LLM first clarifies what the user wants, for example whether they mean lemmas or word forms. It then calls the earlier rule-based translator Alpha to produce CQL, checks and fixes the result, retrieves corpus data, and runs further analysis in Python.

Over roughly 20 months of real use, the tool attracted thousands of API calls without any media promotion. The authors present it as the first corpus interface with voice input. The main lesson they report is that dependence on a third-party platform was costly: unannounced model changes and routing across models of varying quality made the system's behaviour unpredictable. They plan to move to the Model Context Protocol (MCP) to regain control.

Key points

  • Usage: From March 2024 to November 2025, the system made 10,360 API calls across 382 active days, about 27.1 per active day. Usage peaked in November 2024 at 3,258 calls.
  • API endpoints: The CNC-side API offers endpoints such as /translate (Alpha), /concordance (KWIC), /term-frequency (IPM, ARF), /freqs, /collocations (logDice by default), /text-types, /corplist and /info.
  • Languages queried:
    • Written Czech corpora: about 7,200 prompts.
    • Spoken Czech corpora: 250 prompts.
    • English (InterCorp English, BNC): 550 prompts.
    • Smaller counts for German (167), Polish (117), French (68) and others.
  • Recurring errors:
    • Mistakes in CQL syntax.
    • Endpoints that do not exist.
    • Failing to tell users about available features, such as subcorpus comparisons or charts.
    • Under GPT-5.x routing, the system is barely usable in non-thinking mode.
  • Open materials: The system prompt and API description are published on Zenodo and OSF. Planned next steps are migration to MCP, an agentic setup, and less reliance on Alpha.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages · History & humanities

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2026.latechclfl-1.29

@inproceedings{milicka2026ai,
  title = {{AI Corpus Linguist: More than a Year of Experience}},
  author = {Milička, Jiří and Machálek, Tomáš},
  booktitle = {Proceedings of the 10th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature 2026},
  year = {2026},
  doi = {10.18653/v1/2026.latechclfl-1.29},
  url = {https://doi.org/10.18653/v1/2026.latechclfl-1.29}
}

References

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