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README.md
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sequence: string
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- name: evidence_ids
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sequence: string
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- name: labels
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sequence: string
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splits:
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- name: train
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num_bytes:
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num_examples: 206
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download_size:
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dataset_size:
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configs:
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- config_name: distractors
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data_files:
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- 100K<n<1M
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---
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## Process Code
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```python
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"evidence": [],
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"evidence_id": [],
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"label": [],
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}
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for i, row in claims.iterrows():
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data["evidence"].append(id2doc[evidence_id])
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data["evidence_id"].append(evidence_id)
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data["label"].append(label)
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ds = Dataset.from_dict(data)
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distractors = Dataset.from_dict(distractors)
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ds.push_to_hub("umbc-scify/scifact-open", "test")
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distractors.push_to_hub("umbc-scify/scifact-open", "distractors")
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-
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sequence: string
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- name: evidence_ids
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sequence: string
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splits:
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- name: train
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num_bytes: 1168214
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num_examples: 206
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download_size: 555669
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dataset_size: 1168214
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configs:
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- config_name: distractors
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data_files:
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- 100K<n<1M
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---
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## Data Stats
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- 206 claims
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- 500k distractors
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## Data Structure
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### Test
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- claim
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- evidence: GT evidence
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- evidence_id: GT evidence id
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- label: GT label
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- evidences: list of all evidences
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- evidence_ids: list of all evidence ids
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- labels: list of all labels
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### Distractors
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- evidence
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- evidence_id
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## Process Code
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```python
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"evidence": [],
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"evidence_id": [],
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"label": [],
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"evidences": [],
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"evidence_ids": [],
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"labels": [],
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}
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for i, row in claims.iterrows():
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data["evidence"].append(id2doc[evidence_id])
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data["evidence_id"].append(evidence_id)
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data["label"].append(label)
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data["evidences"].append([id2doc[int(eid)] for eid in evidence_ids])
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data["evidence_ids"].append(evidence_ids)
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data["labels"].append(labels)
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ds = Dataset.from_dict(data)
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distractors = Dataset.from_dict(distractors)
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distractors.push_to_hub("umbc-scify/scifact-open", "distractors")
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ds.push_to_hub("umbc-scify/scifact-open", "test")
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```
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