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Data · dataset · 2026

Scope-taking behavior with respect to focusing adverbs

Listed in REDU - Unicamp Institutional Research Data Repository

Description

The data reported herein form part of the FAPESP-funded project (23/16142-0) entitled "Diagnostics for Adverbs: (Micro)variation and Cartography" and test, in three varieties of Portuguese (Angolan (AO), Brazilian (BP) and Mozambican (MOZ)) as well as in two varieties of Spanish (Chilean (CS) and Peruvian (PS)), the placement of each adverb from Cinque's (1999) hierarchy with respect to a focusing adverb. The dataset is organised into four zipped folders, grouped by language family and by file type: - "7 Corpus Scope-Taking Behavior with Respect to Focusing Adverbs (AO, BP, MOZ).zip" — Corpus files containing the sentences in which each adverb cooccurs with a focusing adverb in AO, BP and MOZ, already judged by native speakers of each variety, each with its respective metadata page. - "7 Corpus Scope-Taking Behavior with Respect to Focusing Adverbs (CS, PS).zip" — Corpus files containing the sentences in which each adverb cooccurs with a focusing adverb in CS and PS, already judged by native speakers of each variety, each with its respective metadata page. - "7 Prompts Scope-Taking Behavior with Respect to Focusing Adverbs (AO, BP, MOZ).zip" — Prompt files provided to the AI for the generation and/or linguistic and cultural adaptation of the sentences tested in AO, BP and MOZ.

Each prompt was carefully prepared by the project executor, Prof. Aquiles Tescari Neto, and specifies the nature of the task to be undertaken by the AI, the target construction and the type of sentences to be generated. In this project, the AI was used solely to generate sentences for Brazilian Portuguese and to adapt them to the linguistic and cultural realities of Angola and Mozambique. - "7 Prompts Scope-Taking Behavior with Respect to Focusing Adverbs (CS, PS).zip" — Prompt files provided to the AI for the generation, translation and/or linguistic and cultural adaptation of the sentences tested in CS and PS, following the same procedure as described for the Portuguese varieties.

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Once the data were generated, translated and/or adapted by the AI, they were carefully reviewed by the project executor, Prof. Aquiles Tescari Neto, and submitted to acceptability/grammaticality judgements by native speakers of the respective varieties, following standard practice in Generative Grammar.

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Linguistic structures 75%
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