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Dataset Card for "matinf"

Dataset Summary

MATINF is the first jointly labeled large-scale dataset for classification, question answering and summarization. MATINF contains 1.07 million question-answer pairs with human-labeled categories and user-generated question descriptions. Based on such rich information, MATINF is applicable for three major NLP tasks, including classification, question answering, and summarization. We benchmark existing methods and a novel multi-task baseline over MATINF to inspire further research. Our comprehensive comparison and experiments over MATINF and other datasets demonstrate the merits held by MATINF.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

age_classification

  • Size of downloaded dataset files: 0.00 MB
  • Size of the generated dataset: 48.39 MB
  • Total amount of disk used: 48.39 MB

An example of 'validation' looks as follows.

This example was too long and was cropped:

{
    "description": "\"6个月的时候去儿宝检查,医生说宝宝的分胯动作做的不好,说最好去儿童医院看看,但我家宝宝很好,感觉没有什么不正常啊,请教一下,分胯做的不好,有什么不好吗?\"...",
    "id": 88016,
    "label": 0,
    "question": "医生说宝宝的分胯动作不好"
}

qa

  • Size of downloaded dataset files: 0.00 MB
  • Size of the generated dataset: 268.69 MB
  • Total amount of disk used: 268.69 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "answer": "\"我一个同学的孩子就是发现了肾积水,治疗了一段时间,结果还是越来越多,没办法就打掉了。虽然舍不得,但是还是要忍痛割爱,不然以后孩子真的有问题,大人和孩子都受罪。不过,这个最后的决定还要你自己做,毕竟是你的宝宝。,、、、、\"...",
    "id": 536714,
    "question": "孕5个月检查右侧肾积水孩子能要吗?"
}

summarization

  • Size of downloaded dataset files: 0.00 MB
  • Size of the generated dataset: 258.88 MB
  • Total amount of disk used: 258.88 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "description": "\"宝宝有中度HIE,但原因未查明,这是他出生后脸上红的几道,嘴唇深红近紫,请问这是像缺氧的表现吗?\"...",
    "id": 173649,
    "question": "宝宝脸上红的几道嘴唇深红近紫是像缺氧的表现吗?"
}

topic_classification

  • Size of downloaded dataset files: 0.00 MB
  • Size of the generated dataset: 219.04 MB
  • Total amount of disk used: 219.04 MB

An example of 'train' looks as follows.

{
    "description": "媳妇怀孕五个月了经检查右侧肾积水、过了半月左侧也出现肾积水、她要拿掉孩子、怎么办?",
    "id": 536714,
    "label": 8,
    "question": "孕5个月检查右侧肾积水孩子能要吗?"
}

Data Fields

The data fields are the same among all splits.

age_classification

  • question: a string feature.
  • description: a string feature.
  • label: a classification label, with possible values including 0-1岁 (0), 1-2岁 (1), 2-3岁 (2).
  • id: a int32 feature.

qa

  • question: a string feature.
  • answer: a string feature.
  • id: a int32 feature.

summarization

  • description: a string feature.
  • question: a string feature.
  • id: a int32 feature.

topic_classification

  • question: a string feature.
  • description: a string feature.
  • label: a classification label, with possible values including 产褥期保健 (0), 儿童过敏 (1), 动作发育 (2), 婴幼保健 (3), 婴幼心理 (4).
  • id: a int32 feature.

Data Splits

name train validation test
age_classification 134852 19323 38318
qa 747888 106842 213681
summarization 747888 106842 213681
topic_classification 613036 87519 175363

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

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@inproceedings{xu-etal-2020-matinf,
    title = "{MATINF}: A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and Summarization",
    author = "Xu, Canwen  and
      Pei, Jiaxin  and
      Wu, Hongtao  and
      Liu, Yiyu  and
      Li, Chenliang",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.acl-main.330",
    pages = "3586--3596",
}

Contributions

Thanks to @JetRunner for adding this dataset.

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