README.md

metadata

language:
  - en
paperswithcode_id: doqa
pretty_name: DoQA
dataset_info:
  - config_name: cooking
    features:
      - name: title
        dtype: string
      - name: background
        dtype: string
      - name: context
        dtype: string
      - name: question
        dtype: string
      - name: id
        dtype: string
      - name: answers
        sequence:
          - name: text
            dtype: string
          - name: answer_start
            dtype: int32
      - name: followup
        dtype: string
      - name: yesno
        dtype: string
      - name: orig_answer
        sequence:
          - name: text
            dtype: string
          - name: answer_start
            dtype: int32
    splits:
      - name: test
        num_bytes: 2969064
        num_examples: 1797
      - name: validation
        num_bytes: 1461613
        num_examples: 911
      - name: train
        num_bytes: 6881681
        num_examples: 4612
    download_size: 4197671
    dataset_size: 11312358
  - config_name: movies
    features:
      - name: title
        dtype: string
      - name: background
        dtype: string
      - name: context
        dtype: string
      - name: question
        dtype: string
      - name: id
        dtype: string
      - name: answers
        sequence:
          - name: text
            dtype: string
          - name: answer_start
            dtype: int32
      - name: followup
        dtype: string
      - name: yesno
        dtype: string
      - name: orig_answer
        sequence:
          - name: text
            dtype: string
          - name: answer_start
            dtype: int32
    splits:
      - name: test
        num_bytes: 3166075
        num_examples: 1884
    download_size: 4197671
    dataset_size: 3166075
  - config_name: travel
    features:
      - name: title
        dtype: string
      - name: background
        dtype: string
      - name: context
        dtype: string
      - name: question
        dtype: string
      - name: id
        dtype: string
      - name: answers
        sequence:
          - name: text
            dtype: string
          - name: answer_start
            dtype: int32
      - name: followup
        dtype: string
      - name: yesno
        dtype: string
      - name: orig_answer
        sequence:
          - name: text
            dtype: string
          - name: answer_start
            dtype: int32
    splits:
      - name: test
        num_bytes: 3216374
        num_examples: 1713
    download_size: 4197671
    dataset_size: 3216374

Dataset Card for "doqa"

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/RevanthRameshkumar/CRD3
• Repository: More Information Needed
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 12.59 MB
• Size of the generated dataset: 17.70 MB
• Total amount of disk used: 30.28 MB

Dataset Summary

DoQA is a dataset for accessing Domain Specific FAQs via conversational QA that contains 2,437 information-seeking question/answer dialogues (10,917 questions in total) on three different domains: cooking, travel and movies. Note that we include in the generic concept of FAQs also Community Question Answering sites, as well as corporate information in intranets which is maintained in textual form similar to FAQs, often referred to as internal “knowledge bases”.

These dialogues are created by crowd workers that play the following two roles: the user who asks questions about a given topic posted in Stack Exchange (https://stackexchange.com/), and the domain expert who replies to the questions by selecting a short span of text from the long textual reply in the original post. The expert can rephrase the selected span, in order to make it look more natural. The dataset covers unanswerable questions and some relevant dialogue acts.

DoQA enables the development and evaluation of conversational QA systems that help users access the knowledge buried in domain specific FAQs.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

cooking

• Size of downloaded dataset files: 4.19 MB
• Size of the generated dataset: 11.31 MB
• Total amount of disk used: 15.51 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "answers": {
        "answer_start": [852],
        "text": ["CANNOTANSWER"]
    },
    "background": "\"So, over mixing batter forms gluten, which in turn hardens the cake. Fine.The problem is that I don't want lumps in the cakes, ...",
    "context": "\"Milk won't help you - it's mostly water, and gluten develops from flour (more accurately, specific proteins in flour) and water...",
    "followup": "n",
    "id": "C_64ce44d5f14347f488eb04b50387f022_q#2",
    "orig_answer": {
        "answer_start": [852],
        "text": ["CANNOTANSWER"]
    },
    "question": "Ok. What can I add to make it more softer and avoid hardening?",
    "title": "What to add to the batter of the cake to avoid hardening when the gluten formation can't be avoided?",
    "yesno": "x"
}

movies

• Size of downloaded dataset files: 4.19 MB
• Size of the generated dataset: 3.17 MB
• Total amount of disk used: 7.36 MB

An example of 'test' looks as follows.

This example was too long and was cropped:

{
    "answers": {
        "answer_start": [852],
        "text": ["CANNOTANSWER"]
    },
    "background": "\"So, over mixing batter forms gluten, which in turn hardens the cake. Fine.The problem is that I don't want lumps in the cakes, ...",
    "context": "\"Milk won't help you - it's mostly water, and gluten develops from flour (more accurately, specific proteins in flour) and water...",
    "followup": "n",
    "id": "C_64ce44d5f14347f488eb04b50387f022_q#2",
    "orig_answer": {
        "answer_start": [852],
        "text": ["CANNOTANSWER"]
    },
    "question": "Ok. What can I add to make it more softer and avoid hardening?",
    "title": "What to add to the batter of the cake to avoid hardening when the gluten formation can't be avoided?",
    "yesno": "x"
}

travel

• Size of downloaded dataset files: 4.19 MB
• Size of the generated dataset: 3.22 MB
• Total amount of disk used: 7.41 MB

An example of 'test' looks as follows.

This example was too long and was cropped:

{
    "answers": {
        "answer_start": [852],
        "text": ["CANNOTANSWER"]
    },
    "background": "\"So, over mixing batter forms gluten, which in turn hardens the cake. Fine.The problem is that I don't want lumps in the cakes, ...",
    "context": "\"Milk won't help you - it's mostly water, and gluten develops from flour (more accurately, specific proteins in flour) and water...",
    "followup": "n",
    "id": "C_64ce44d5f14347f488eb04b50387f022_q#2",
    "orig_answer": {
        "answer_start": [852],
        "text": ["CANNOTANSWER"]
    },
    "question": "Ok. What can I add to make it more softer and avoid hardening?",
    "title": "What to add to the batter of the cake to avoid hardening when the gluten formation can't be avoided?",
    "yesno": "x"
}

Data Fields

The data fields are the same among all splits.

cooking

• title: a string feature.
• background: a string feature.
• context: a string feature.
• question: a string feature.
• id: a string feature.
• answers: a dictionary feature containing:
  • text: a string feature.
  • answer_start: a int32 feature.
• followup: a string feature.
• yesno: a string feature.
• orig_answer: a dictionary feature containing:
  • text: a string feature.
  • answer_start: a int32 feature.

movies

• title: a string feature.
• background: a string feature.
• context: a string feature.
• question: a string feature.
• id: a string feature.
• answers: a dictionary feature containing:
  • text: a string feature.
  • answer_start: a int32 feature.
• followup: a string feature.
• yesno: a string feature.
• orig_answer: a dictionary feature containing:
  • text: a string feature.
  • answer_start: a int32 feature.

travel

• title: a string feature.
• background: a string feature.
• context: a string feature.
• question: a string feature.
• id: a string feature.
• answers: a dictionary feature containing:
  • text: a string feature.
  • answer_start: a int32 feature.
• followup: a string feature.
• yesno: a string feature.
• orig_answer: a dictionary feature containing:
  • text: a string feature.
  • answer_start: a int32 feature.

Data Splits

cooking

	train	validation	test
cooking	4612	911	1797

movies

	test
movies	1884

travel

	test
travel	1713

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

@misc{campos2020doqa,
    title={DoQA -- Accessing Domain-Specific FAQs via Conversational QA},
    author={Jon Ander Campos and Arantxa Otegi and Aitor Soroa and Jan Deriu and Mark Cieliebak and Eneko Agirre},
    year={2020},
    eprint={2005.01328},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

Contributions

Thanks to @mariamabarham, @thomwolf, @lhoestq for adding this dataset.