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README.md

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+---
+license: mit
+task_categories:
+  - text-classification
+  - multimodal
+language:
+  - en
+tags:
+  - fact-checking
+  - mocheg
+  - multimodal
+---
+
+# mocheg-multimodal
+
+This is a HuggingFace-ready version of the **MOCHEG** multimodal fact-checking dataset.
+
+## Structure
+
+- `train.json`: One row per (claim, evidence)
+- `images/`: Sharded image evidence
+- `*_qrels.csv`: Original retrieval relevance files
+
+## Fields (train.json)
+
+- `claim_id`
+- `claim`
+- `evidence_id`
+- `text_evidence`
+- `label` (support / refute / not enough information)
+- `ruling_outline`
+- `origin`
+- `snopes_url`
+- `image` (relative path)
+
+## Citation
+
+Please cite the original MOCHEG paper if you use this dataset.

load_dataset.py

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+import json
+from pathlib import Path
+from PIL import Image
+
+def load_mocheg(data_dir: str):
+    data_dir = Path(data_dir)
+    with open(data_dir / "train.json") as f:
+        data = json.load(f)
+
+    for sample in data:
+        if sample.get("image"):
+            img_path = data_dir / sample["image"]
+            sample["image_data"] = Image.open(img_path) if img_path.exists() else None
+        else:
+            sample["image_data"] = None
+
+    return data