ProText: A benchmark dataset for measuring (mis)gendering in long-form texts
We introduce ProText, a dataset for measuring gendering and misgendering in stylistically diverse long-form English texts. ProText spans three dimensions: Theme nouns (names, occupations, titles, kinship terms), Theme category (stereotypically male, stereotypically female, gender-neutral/non-gendered), and Pronoun category (masculine, feminine, gender-neutral, none). The dataset is designed to probe (mis)gendering in text transformations such as summarization and rewrites using state-of-the-art Large Language Models, extending beyond traditional pronoun resolution benchmarks and beyond the gender binary. We validated ProText through a mini case study, showing that even with just two promp...
| Authors | Hadas Kotek, Margit Bowler, Patrick Sonnenberg et al. |
|---|---|
| Primary category | cs.CL |
| Published | 29 March 2026 |
| Last updated at source | 29 March 2026 |
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