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metadata
annotations_creators:
  - found
language:
  - en
language_creators:
  - found
license:
  - unknown
multilinguality:
  - monolingual
pretty_name: UDC (Ubuntu Dialogue Corpus)
size_categories:
  - 1M<n<10M
source_datasets:
  - original
task_categories:
  - conversational
task_ids:
  - dialogue-generation
paperswithcode_id: ubuntu-dialogue-corpus
dataset_info:
  - config_name: train
    features:
      - name: Context
        dtype: string
      - name: Utterance
        dtype: string
      - name: Label
        dtype: int32
    splits:
      - name: train
        num_bytes: 525126729
        num_examples: 1000000
    download_size: 0
    dataset_size: 525126729
  - config_name: dev_test
    features:
      - name: Context
        dtype: string
      - name: Ground Truth Utterance
        dtype: string
      - name: Distractor_0
        dtype: string
      - name: Distractor_1
        dtype: string
      - name: Distractor_2
        dtype: string
      - name: Distractor_3
        dtype: string
      - name: Distractor_4
        dtype: string
      - name: Distractor_5
        dtype: string
      - name: Distractor_6
        dtype: string
      - name: Distractor_7
        dtype: string
      - name: Distractor_8
        dtype: string
    splits:
      - name: test
        num_bytes: 27060502
        num_examples: 18920
      - name: validation
        num_bytes: 27663181
        num_examples: 19560
    download_size: 0
    dataset_size: 54723683

Dataset Card for "ubuntu_dialogs_corpus"

Table of Contents

Dataset Description

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

More Information Needed

Dataset Structure

Data Instances

train

  • Size of downloaded dataset files: 0.00 MB
  • Size of the generated dataset: 62.46 MB
  • Total amount of disk used: 62.46 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

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

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.