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---
dataset_info:
- config_name: distractors
features:
- name: evidence
dtype: string
- name: evidence_id
dtype: int64
splits:
- name: train
num_bytes: 735316804
num_examples: 500000
download_size: 417661627
dataset_size: 735316804
- config_name: test
features:
- name: claim
dtype: string
- name: evidence
dtype: string
- name: evidence_id
dtype: int64
- name: label
dtype: string
- name: evidences
sequence: string
- name: evidence_ids
sequence: string
- name: labels
sequence: string
splits:
- name: train
num_bytes: 1174731
num_examples: 206
download_size: 556372
dataset_size: 1174731
configs:
- config_name: distractors
data_files:
- split: train
path: distractors/train-*
- config_name: test
data_files:
- split: train
path: test/train-*
size_categories:
- 100K<n<1M
---
## Data Stats
- 206 claims
- 500k distractors
## Data Structure
### Test
- claim
- evidence: GT evidence
- evidence_id: GT evidence id
- label: GT label
- evidences: list of all evidences
- evidence_ids: list of all evidence ids
- labels: list of all labels
### Distractors
- evidence
- evidence_id
## Process Code
```python
import pandas as pd
from datasets import Dataset
claims = pd.read_csv("./scifact_open_retriever_test.csv")
claims.head()
docs = pd.read_csv("./scifact_open_docs.csv")
docs.head()
id2doc = dict(zip(docs["ID"], docs["Doc"]))
data = {
"claim": [],
"evidence": [],
"evidence_id": [],
"label": [],
"evidences": [],
"evidence_ids": [],
"labels": [],
}
for i, row in claims.iterrows():
data["claim"].append(row["Query"])
evidence_ids = eval(row["Gold"])
evidence_id = int(evidence_ids[0])
labels = eval(row["Label"])
label = str(labels[0])
data["evidence"].append(id2doc[evidence_id])
data["evidence_id"].append(evidence_id)
data["label"].append(label)
data["evidences"].append([id2doc[int(eid)] for eid in evidence_ids])
data["evidence_ids"].append(evidence_ids)
data["labels"].append(labels)
ds = Dataset.from_dict(data)
distractors = {
"evidence": [],
"evidence_id": [],
}
for i, row in docs.iterrows():
distractors["evidence"].append(row["Doc"])
distractors["evidence_id"].append(row["ID"])
distractors = Dataset.from_dict(distractors)
distractors.push_to_hub("umbc-scify/scifact-open", "distractors")
ds.push_to_hub("umbc-scify/scifact-open", "test")
```
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