README.md

metadata

paperswithcode_id: matinf
pretty_name: Maternal and Infant Dataset
dataset_info:
  - config_name: age_classification
    features:
      - name: question
        dtype: string
      - name: description
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': 0-1岁
              '1': 1-2岁
              '2': 2-3岁
      - name: id
        dtype: int32
    splits:
      - name: test
        num_bytes: 9616194
        num_examples: 38318
      - name: train
        num_bytes: 33901977
        num_examples: 134852
      - name: validation
        num_bytes: 4869685
        num_examples: 19323
    download_size: 0
    dataset_size: 48387856
  - config_name: topic_classification
    features:
      - name: question
        dtype: string
      - name: description
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': 产褥期保健
              '1': 儿童过敏
              '2': 动作发育
              '3': 婴幼保健
              '4': 婴幼心理
              '5': 婴幼早教
              '6': 婴幼期喂养
              '7': 婴幼营养
              '8': 孕期保健
              '9': 家庭教育
              '10': 幼儿园
              '11': 未准父母
              '12': 流产和不孕
              '13': 疫苗接种
              '14': 皮肤护理
              '15': 宝宝上火
              '16': 腹泻
              '17': 婴幼常见病
      - name: id
        dtype: int32
    splits:
      - name: test
        num_bytes: 43877443
        num_examples: 175363
      - name: train
        num_bytes: 153326538
        num_examples: 613036
      - name: validation
        num_bytes: 21834951
        num_examples: 87519
    download_size: 0
    dataset_size: 219038932
  - config_name: summarization
    features:
      - name: description
        dtype: string
      - name: question
        dtype: string
      - name: id
        dtype: int32
    splits:
      - name: test
        num_bytes: 51784189
        num_examples: 213681
      - name: train
        num_bytes: 181245403
        num_examples: 747888
      - name: validation
        num_bytes: 25849900
        num_examples: 106842
    download_size: 0
    dataset_size: 258879492
  - config_name: qa
    features:
      - name: question
        dtype: string
      - name: answer
        dtype: string
      - name: id
        dtype: int32
    splits:
      - name: test
        num_bytes: 53708532
        num_examples: 213681
      - name: train
        num_bytes: 188047511
        num_examples: 747888
      - name: validation
        num_bytes: 26931809
        num_examples: 106842
    download_size: 0
    dataset_size: 268687852

Dataset Card for "matinf"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://github.com/WHUIR/MATINF
• Repository: More Information Needed
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 0.00 MB
• Size of the generated dataset: 758.17 MB
• Total amount of disk used: 758.17 MB

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: 46.15 MB
• Total amount of disk used: 46.15 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: 256.24 MB
• Total amount of disk used: 256.24 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: 246.89 MB
• Total amount of disk used: 246.89 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: 208.89 MB
• Total amount of disk used: 208.89 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

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

@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.