Dataset Card for "ubuntu_dialogs_corpus"

Dataset Summary

Ubuntu Dialogue Corpus, a dataset containing almost 1 million multi-turn dialogues, with a total of over 7 million utterances and 100 million words. This provides a unique resource for research into building dialogue managers based on neural language models that can make use of large amounts of unlabeled data. The dataset has both the multi-turn property of conversations in the Dialog State Tracking Challenge datasets, and the unstructured nature of interactions from microblog services such as Twitter.

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

train

• Size of downloaded dataset files: 0.00 MB
• Size of the generated dataset: 65.49 MB
• Total amount of disk used: 65.49 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "Context": "\"i think we could import the old comment via rsync , but from there we need to go via email . i think it be easier than cach the...",
    "Label": 1,
    "Utterance": "basic each xfree86 upload will not forc user to upgrad 100mb of font for noth __eou__ no someth i do in my spare time . __eou__"
}

Data Fields

The data fields are the same among all splits.

train

• Context : a string feature.
• Utterance : a string feature.
• Label : a int32 feature.

Data Splits

name	train
train	127422

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@article{DBLP:journals/corr/LowePSP15,
  author    = {Ryan Lowe and
               Nissan Pow and
               Iulian Serban and
               Joelle Pineau},
  title     = {The Ubuntu Dialogue Corpus: {A} Large Dataset for Research in Unstructured
               Multi-Turn Dialogue Systems},
  journal   = {CoRR},
  volume    = {abs/1506.08909},
  year      = {2015},
  url       = {http://arxiv.org/abs/1506.08909},
  archivePrefix = {arXiv},
  eprint    = {1506.08909},
  timestamp = {Mon, 13 Aug 2018 16:48:23 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/LowePSP15.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Contributions

Thanks to @thomwolf , @patrickvonplaten , @lewtun for adding this dataset.