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Dataset: doqa 🏷
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Dataset Card for "doqa"

Table of Contents

Dataset Description

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

More Information Needed

Languages

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Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

cooking

  • Size of downloaded dataset files: 4.00 MB
  • Size of the generated dataset: 10.79 MB
  • Total amount of disk used: 14.79 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: 4.00 MB
  • Size of the generated dataset: 3.02 MB
  • Total amount of disk used: 7.02 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: 4.00 MB
  • Size of the generated dataset: 3.07 MB
  • Total amount of disk used: 7.07 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 Sample Size

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

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Annotations

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

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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


@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}
}