q_re_cc
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Kumpulan data yang berisi 14 ribu percakapan dengan 81 ribu pasangan tanya jawab. QReCC dibuat berdasarkan pertanyaan dari TREC CAsT, QuAC, dan Google Natural Questions.
Membelah | Contoh |
---|
'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.),
})
Fitur | Kelas | Membentuk | Tipe D | Keterangan |
---|
| FiturDict | | | |
menjawab | Teks | | rangkaian | |
jawaban_url | Teks | | rangkaian | |
konteks | Urutan (Teks) | (Tidak ada,) | rangkaian | |
percakapan_id | Skalar | | int32 | Id percakapan. |
pertanyaan | Teks | | rangkaian | |
pertanyaan_tulis ulang | Teks | | rangkaian | |
sumber | Teks | | rangkaian | Sumber data asli -- QuAC, CAST, atau Natural Questions |
turn_id | Skalar | | int32 | Id percakapan berubah, dalam percakapan. |
@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}
}
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
Terakhir diperbarui pada 2024-09-04 UTC.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Informasi yang saya butuhkan tidak ada","missingTheInformationINeed","thumb-down"],["Terlalu rumit/langkahnya terlalu banyak","tooComplicatedTooManySteps","thumb-down"],["Sudah usang","outOfDate","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Masalah kode / contoh","samplesCodeIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2024-09-04 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 }"]]