This dataset contains a corpus of 329 annotated conversations between Italian university students (EFL learners) and AI-based chatbots (ChatGPT and Pi.AI), collected between May and December 2024 within the PRIN 2022 project *UNITE – Universally Inclusive Technologies to Practice English*. The corpus includes interactions from three institutions (University of Bologna, University of Macerata, and University of Naples “L’Orientale”) and consists of learner-driven tasks such as small talk and role-play activities. All conversations are annotated using a custom semantic tagset (DIS-TAG). DIS-TAG identifies lexical and discourse features related to mobility, sensory perception, and instructional language, enabling the analysis of normative discourse patterns in chatbot responses.
annotated_UNITE_corpus
Valentina De Brasi;Serena Cecchini;Anna Mongibello
2026-01-01
Abstract
This dataset contains a corpus of 329 annotated conversations between Italian university students (EFL learners) and AI-based chatbots (ChatGPT and Pi.AI), collected between May and December 2024 within the PRIN 2022 project *UNITE – Universally Inclusive Technologies to Practice English*. The corpus includes interactions from three institutions (University of Bologna, University of Macerata, and University of Naples “L’Orientale”) and consists of learner-driven tasks such as small talk and role-play activities. All conversations are annotated using a custom semantic tagset (DIS-TAG). DIS-TAG identifies lexical and discourse features related to mobility, sensory perception, and instructional language, enabling the analysis of normative discourse patterns in chatbot responses.| File | Dimensione | Formato | |
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annotated_UNITE_corpus.zip
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