Datasets:

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Multilinguality:
monolingual
Size Categories:
1M<n<10M
Language Creators:
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Annotations Creators:
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Update files from the datasets library (from 1.7.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.7.0

Files changed (1) hide show
  1. README.md +17 -4
README.md CHANGED
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  # Dataset Card for "ubuntu_dialogs_corpus"
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
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  - [Dataset Summary](#dataset-summary)
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- - [Supported Tasks](#supported-tasks)
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  - [Languages](#languages)
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Fields](#data-fields)
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- - [Data Splits Sample Size](#data-splits-sample-size)
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  - [Dataset Creation](#dataset-creation)
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  - [Curation Rationale](#curation-rationale)
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  - [Source Data](#source-data)
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  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.
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- ### Supported Tasks
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  - `Utterance`: a `string` feature.
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  - `Label`: a `int32` feature.
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- ### Data Splits Sample Size
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  |name |train |
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  |-----|-----:|
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  ### Source Data
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ### Annotations
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ### Personal and Sensitive Information
 
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+ paperswithcode_id: ubuntu-dialogue-corpus
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  ---
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  # Dataset Card for "ubuntu_dialogs_corpus"
 
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
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  - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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  - [Languages](#languages)
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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  - [Dataset Creation](#dataset-creation)
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  - [Curation Rationale](#curation-rationale)
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  - [Source Data](#source-data)
 
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  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.
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+ ### Supported Tasks and Leaderboards
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  - `Utterance`: a `string` feature.
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  - `Label`: a `int32` feature.
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+ ### Data Splits
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  |name |train |
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  |-----|-----:|
 
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  ### Source Data
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+ #### Initial Data Collection and Normalization
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+ #### Who are the source language producers?
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ### Annotations
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+ #### Annotation process
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+ #### Who are the annotators?
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ### Personal and Sensitive Information