Publish Nordet benchmark dataset

README.md

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 ---
-license: cc0-1.0
+pretty_name: Nordet Social Cognition Benchmark
+language:
+  - fr
+  - en
+task_categories:
+  - question-answering
+  - visual-question-answering
+tags:
+  - benchmark
+  - social-cognition
+  - quebec
+  - multimodal
+size_categories:
+  - n<1K
 ---
+
+# Nordet Social Cognition Benchmark
+
+Nordet evaluates social cognition in culturally and historically situated Quebec contexts.
+It contains 381 challenge and control examples across four tasks:
+
+- literal vs. intent;
+- historical and social inference;
+- communication adaptation;
+- cultural understanding.
+
+The dataset combines text, transcribed spoken language, and 57 embedded images. Questions are
+provided in French and English. Every row includes a reference answer, source citation, and a
+reproducible LLM-as-a-judge prompt template.
+
+## Loading
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Pythonner/nordet", split="train")
+```
+
+For multimodal examples, `image` is decoded as a PIL image. Text-only examples contain `None`.
+The `messages` column follows the Hugging Face conversational vision format; an image content
+marker identifies where the corresponding `image` belongs in the user message.
+
+## Variants
+
+The `variant` column distinguishes `challenge` from `control`. Controls preserve the general
+question and evaluation shape while reducing the culturally situated social inference required.
+
+## Evaluation
+
+Replace `{response_text}` in `llm_as_a_judge_prompt_template` with the evaluated model response:
+
+```python
+judge_prompt = row["llm_as_a_judge_prompt_template"].replace(
+    "{response_text}", model_response
+)
+```
+
+The template requests a structured result for every criterion. Reference answers are included in
+the criteria where the original Kaggle benchmark used them for judge calibration.
+
+## Sources and rights
+
+Questions were authored for Nordet. Reference answers are grounded in the cited source material.
+Images retain their original source URLs and should be used according to the rights identified by
+their respective source repositories, including BAnQ and Wikimedia Commons.
+
+See the final project writeup:
+<https://www.kaggle.com/competitions/kaggle-measuring-agi/writeups/nordet-social-cognition-benchmark>

data/train.parquet

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