Dataset:
sharc_modified

Task Categories: question-answering
Languages: en
Multilinguality: monolingual
Size Categories: 10K<n<100K
Licenses: unknown
Language Creators: crowdsourcedexpert-generated
Annotations Creators: crowdsourced
Source Datasets: extended|sharc

Dataset Card Creation Guide

Dataset Summary

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Supported Tasks and Leaderboards

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Languages

The dataset is in english (en).

Dataset Structure

Data Instances

Example of one instance:

{
    "annotation": {
        "answer": [
            {
                "paragraph_reference": {
                    "end": 64,
                    "start": 35,
                    "string": "syndactyly affecting the feet"
                },
                "sentence_reference": {
                    "bridge": false,
                    "end": 64,
                    "start": 35,
                    "string": "syndactyly affecting the feet"
                }
            }
        ],
        "explanation_type": "single_sentence",
        "referential_equalities": [
            {
                "question_reference": {
                    "end": 40,
                    "start": 29,
                    "string": "webbed toes"
                },
                "sentence_reference": {
                    "bridge": false,
                    "end": 11,
                    "start": 0,
                    "string": "Webbed toes"
                }
            }
        ],
        "selected_sentence": {
            "end": 67,
            "start": 0,
            "string": "Webbed toes is the common name for syndactyly affecting the feet . "
        }
    },
    "example_id": 9174646170831578919,
    "original_nq_answers": [
        {
            "end": 45,
            "start": 35,
            "string": "syndactyly"
        }
    ],
    "paragraph_text": "Webbed toes is the common name for syndactyly affecting the feet . It is characterised by the fusion of two or more digits of the feet . This is normal in many birds , such as ducks ; amphibians , such as frogs ; and mammals , such as kangaroos . In humans it is considered unusual , occurring in approximately one in 2,000 to 2,500 live births .",
    "question": "what is the medical term for webbed toes",
    "sentence_starts": [
        0,
        67,
        137,
        247
    ],
    "title_text": "Webbed toes",
    "url": "https: //en.wikipedia.org//w/index.php?title=Webbed_toes&amp;oldid=801229780"
}

Data Fields

  • example_id: a unique integer identifier that matches up with NQ
  • title_text: the title of the wikipedia page containing the paragraph
  • url: the url of the wikipedia page containing the paragraph
  • question: a natural language question string from NQ
  • paragraph_text: a paragraph string from a wikipedia page containing the answer to question
  • sentence_starts: a list of integer character offsets indicating the start of sentences in the paragraph
  • original_nq_answers: the original short answer spans from NQ
  • annotation: the QED annotation, a dictionary with the following items and further elaborated upon below:
    • referential_equalities: a list of dictionaries, one for each referential equality link annotated
    • answer: a list of dictionaries, one for each short answer span
    • selected_sentence: a dictionary representing the annotated sentence in the passage
    • explanation_type: one of "single_sentence", "multi_sentence", or "none"

Data Splits

The dataset is split into training and validation splits. | | Tain | Valid | | ----- | ------ | ----- | | N. Instances | 7638 | 1355 |

Dataset Creation

Curation Rationale

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Source Data

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Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

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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

@misc{lamm2020qed,
    title={QED: A Framework and Dataset for Explanations in Question Answering},
    author={Matthew Lamm and Jennimaria Palomaki and Chris Alberti and Daniel Andor and Eunsol Choi and Livio Baldini Soares and Michael Collins},
    year={2020},
    eprint={2009.06354},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

Contributions

Thanks to @patil-suraj for adding this dataset.

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