q_re_cc
קל לארגן דפים בעזרת אוספים
אפשר לשמור ולסווג תוכן על סמך ההעדפות שלך.
מערך נתונים המכיל 14K שיחות עם 81K צמדי שאלות ותשובות. QReCC בנוי על שאלות של TREC CAsT, QuAC ו-Google Natural Questions.
לְפַצֵל | דוגמאות |
---|
'test' | 16,451 |
'train' | 63,501 |
FeaturesDict({
'answer': Text(shape=(), dtype=string),
'answer_url': Text(shape=(), dtype=string),
'context': Sequence(Text(shape=(), dtype=string)),
'conversation_id': Scalar(shape=(), dtype=int32, description=The id of the conversation.),
'question': Text(shape=(), dtype=string),
'question_rewrite': Text(shape=(), dtype=string),
'source': Text(shape=(), dtype=string),
'turn_id': Scalar(shape=(), dtype=int32, description=The id of the conversation turn, within a conversation.),
})
תכונה | מַחלָקָה | צוּרָה | Dtype | תֵאוּר |
---|
| FeaturesDict | | | |
תְשׁוּבָה | טֶקסט | | חוּט | |
answer_url | טֶקסט | | חוּט | |
הֶקשֵׁר | רצף (טקסט) | (אַף לֹא אֶחָד,) | חוּט | |
שיחה_מזהה | סקלר | | int32 | מזהה השיחה. |
שְׁאֵלָה | טֶקסט | | חוּט | |
שאלה_שכתוב | טֶקסט | | חוּט | |
מָקוֹר | טֶקסט | | חוּט | המקור המקורי של הנתונים - QuAC, CAsT או Natural Questions |
turn_id | סקלר | | int32 | המזהה של סיבוב השיחה, בתוך שיחה. |
@article{qrecc,
title={Open-Domain Question Answering Goes Conversational via Question Rewriting},
author={Anantha, Raviteja and Vakulenko, Svitlana and Tu, Zhucheng and Longpre, Shayne and Pulman, Stephen and Chappidi, Srinivas},
journal={Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
year={2021}
}
אלא אם צוין אחרת, התוכן של דף זה הוא ברישיון Creative Commons Attribution 4.0 ודוגמאות הקוד הן ברישיון Apache 2.0. לפרטים, ניתן לעיין במדיניות האתר Google Developers. Java הוא סימן מסחרי רשום של חברת Oracle ו/או של השותפים העצמאיים שלה.
עדכון אחרון: 2024-09-04 (שעון UTC).
[null,null,["עדכון אחרון: 2024-09-04 (שעון UTC)."],[],[],null,["# q_re_cc\n\n\u003cbr /\u003e\n\n- **Description**:\n\nA dataset containing 14K conversations with 81K question-answer pairs. QReCC is\nbuilt on questions from TREC CAsT, QuAC and Google Natural Questions.\n\n- **Homepage** :\n \u003chttps://github.com/apple/ml-qrecc\u003e\n\n- **Source code** :\n [`tfds.text.qrecc.QReCC`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/text/qrecc/qrecc.py)\n\n- **Versions**:\n\n - **`1.0.0`** (default): Initial release.\n- **Download size** : `7.60 MiB`\n\n- **Dataset size** : `69.29 MiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n Yes\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'test'` | 16,451 |\n| `'train'` | 63,501 |\n\n- **Feature structure**:\n\n FeaturesDict({\n 'answer': Text(shape=(), dtype=string),\n 'answer_url': Text(shape=(), dtype=string),\n 'context': Sequence(Text(shape=(), dtype=string)),\n 'conversation_id': Scalar(shape=(), dtype=int32, description=The id of the conversation.),\n 'question': Text(shape=(), dtype=string),\n 'question_rewrite': Text(shape=(), dtype=string),\n 'source': Text(shape=(), dtype=string),\n 'turn_id': Scalar(shape=(), dtype=int32, description=The id of the conversation turn, within a conversation.),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|------------------|----------------|---------|--------|---------------------------------------------------------------------------|\n| | FeaturesDict | | | |\n| answer | Text | | string | |\n| answer_url | Text | | string | |\n| context | Sequence(Text) | (None,) | string | |\n| conversation_id | Scalar | | int32 | The id of the conversation. |\n| question | Text | | string | |\n| question_rewrite | Text | | string | |\n| source | Text | | string | The original source of the data -- either QuAC, CAsT or Natural Questions |\n| turn_id | Scalar | | int32 | The id of the conversation turn, within a conversation. |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `None`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Examples**\n ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\n- **Citation**:\n\n @article{qrecc,\n title={Open-Domain Question Answering Goes Conversational via Question Rewriting},\n author={Anantha, Raviteja and Vakulenko, Svitlana and Tu, Zhucheng and Longpre, Shayne and Pulman, Stephen and Chappidi, Srinivas},\n journal={Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},\n year={2021}\n }"]]