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configs:
- config_name: default
data_files:
- split: test
path: test.jsonl
- split: dev
path: dev.jsonl
- split: dev_fewshot
path: dev_fewshot.jsonl
license: cc-by-nc-sa-4.0
---
# GSI:detect unified multiple-choice dataset
Each JSONL row represents one original GSI:detect text and has this schema:
```json
{
"Id": 1,
"Question": "...",
"Values": {"A": "0", "B": "0.25", "C": "0.5", "D": "0.75", "E": "1", "Correct": "A"},
"Categories": {"A": "role", "B": "personality", "C": "competence", "D": "physical", "E": "sexual", "F": "relational", "Correct": "C"}
}
```
For original rows with `gs_category: "no"`, `Categories` is JSON `null` rather
than a seventh category. The `Values` mapping is always A=0, B=0.25, C=0.5,
D=0.75, E=1. The category mapping is always A=role, B=personality,
C=competence, D=physical, E=sexual, F=relational.
`test.jsonl` contains the original 810 test rows in original order and is
assigned IDs 1--810. `dev.jsonl` contains the original 200 development rows in
original order and is assigned IDs 811--1010. No items are moved between
splits or removed.
`dev_fewshot.jsonl` contains copies of six `dev` items. Its first five items
are the first occurrence in the original dev split of each GS value, ordered by
value: 0, 0.25, 0.5, 0.75, 1. The corresponding source IDs are
GS0516, GS0458, GS0953, GS0432, and GS0414 respectively. The sixth item is
GS0479 (GS value 0.5, category `personality`): it is the first original dev
item whose non-null category is not represented among the first five items.
With a first_n sampler, the Value task therefore uses the first five examples;
the Category task filters out the null-category GS0516 item and retains five
categorized examples.
## Citation
If you use this dataset, please cite:
Comandini, Gloria, Manuela Speranza, Sofia Brenna, Davide Testa, Stefania Cavagnoli, and Bernardo Magnini. 2026. "GSI:detect at EVALITA 2026: Overview of the Task on Detecting Gender Stereotypes in Italian." In *Proceedings of the Ninth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2026)*, pages 96–108, Bari, Italy. CEUR Workshop Proceedings.
**Official task website:** https://gsi-d-evalita.fbk.eu/
## Credits
EVALITA-LLM dataset adaptation: Pietro Botarelli. |