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README.md
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# Dataset Card for KVRET
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- **Repository:** https://nlp.stanford.edu/blog/a-new-multi-turn-multi-domain-task-oriented-dialogue-dataset/
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- **Leaderboard:** None
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- **Who transforms the dataset:** Qi Zhu(zhuq96 at gmail dot com)
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### Dataset Summary
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In an effort to help alleviate this problem, we release a corpus of 3,031 multi-turn dialogues in three distinct domains appropriate for an in-car assistant: calendar scheduling, weather information retrieval, and point-of-interest navigation. Our dialogues are grounded through knowledge bases ensuring that they are versatile in their natural language without being completely free form.
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---
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language:
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- en
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license: []
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multilinguality:
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- monolingual
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pretty_name: KVRET
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size_categories:
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- 1K<n<10K
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task_categories:
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- conversational
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---
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# Dataset Card for KVRET
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- **Repository:** https://nlp.stanford.edu/blog/a-new-multi-turn-multi-domain-task-oriented-dialogue-dataset/
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- **Leaderboard:** None
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- **Who transforms the dataset:** Qi Zhu(zhuq96 at gmail dot com)
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To use this dataset, you need to install [ConvLab-3](https://github.com/ConvLab/ConvLab-3) platform first. Then you can load the dataset via:
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```
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from convlab.util import load_dataset, load_ontology, load_database
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dataset = load_dataset('kvret')
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ontology = load_ontology('kvret')
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database = load_database('kvret')
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```
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For more usage please refer to [here](https://github.com/ConvLab/ConvLab-3/tree/master/data/unified_datasets).
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### Dataset Summary
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In an effort to help alleviate this problem, we release a corpus of 3,031 multi-turn dialogues in three distinct domains appropriate for an in-car assistant: calendar scheduling, weather information retrieval, and point-of-interest navigation. Our dialogues are grounded through knowledge bases ensuring that they are versatile in their natural language without being completely free form.
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