参考文献:
平文
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:quac/plain_text')
- 説明：
Question Answering in Context is a dataset for modeling, understanding,
and participating in information seeking dialog. Data instances consist
of an interactive dialog between two crowd workers: (1) a student who
poses a sequence of freeform questions to learn as much as possible
about a hidden Wikipedia text, and (2) a teacher who answers the questions
by providing short excerpts (spans) from the text. QuAC introduces
challenges not found in existing machine comprehension datasets: its
questions are often more open-ended, unanswerable, or only meaningful
within the dialog context.
- ライセンス: MIT
- バージョン: 1.1.0
- 分割:
| スプリット | 例 |
|---|---|
'train' | 11567 |
'validation' | 1000 |
- 特徴：
{
"dialogue_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"wikipedia_page_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"background": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"section_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"turn_ids": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"questions": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"followups": {
"feature": {
"num_classes": 3,
"names": [
"y",
"n",
"m"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"yesnos": {
"feature": {
"num_classes": 3,
"names": [
"y",
"n",
"x"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"answers": {
"feature": {
"texts": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"answer_starts": {
"feature": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"orig_answers": {
"texts": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"answer_starts": {
"feature": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
}