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YAML Metadata Warning: The task_categories "conversational" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, other

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

More Information Needed

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

More Information Needed

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

More Information Needed

Additional Information

Dataset Curators

More Information Needed

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.

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