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empathetic_dialogues

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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, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, 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-ranking, 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, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Dataset Card for "empathetic_dialogues"

Dataset Summary

PyTorch original implementation of Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

Size of downloaded dataset files: 28.02 MB
Size of the generated dataset: 25.13 MB
Total amount of disk used: 53.15 MB

An example of 'train' looks as follows.

{
    "context": "sentimental",
    "conv_id": "hit:0_conv:1",
    "prompt": "I remember going to the fireworks with my best friend. There was a lot of people_comma_ but it only felt like us in the world.",
    "selfeval": "5|5|5_2|2|5",
    "speaker_idx": 1,
    "tags": "",
    "utterance": "I remember going to see the fireworks with my best friend. It was the first time we ever spent time alone together. Although there was a lot of people_comma_ we felt like the only people in the world.",
    "utterance_idx": 1
}

Data Fields

The data fields are the same among all splits.

default

conv_id: a string feature.
utterance_idx: a int32 feature.
context: a string feature.
prompt: a string feature.
speaker_idx: a int32 feature.
utterance: a string feature.
selfeval: a string feature.
tags: a string feature.

Data Splits

name	train	validation	test
default	76673	12030	10943

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

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

More Information Needed

Licensing Information

Creative Commons Attribution-NonCommercial 4.0 International.

Citation Information

@inproceedings{rashkin-etal-2019-towards,
    title = "Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset",
    author = "Rashkin, Hannah  and
      Smith, Eric Michael  and
      Li, Margaret  and
      Boureau, Y-Lan",
    booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P19-1534",
    doi = "10.18653/v1/P19-1534",
    pages = "5370--5381",
}