README.md

metadata

annotations_creators:
  - crowdsourced
language_creators:
  - crowdsourced
  - expert-generated
languages:
  - en
licenses:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - extended|sharc
task_categories:
  - question-answering
task_ids:
  - extractive-qa
  - question-answering-other-conversational-qa

Dataset Card Creation Guide

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • 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

Dataset Description

• Homepage: [More info needed]
• Repository: github
• Paper: Neural Conversational QA: Learning to Reason v.s. Exploiting Patterns
• Leaderboard: [More info needed]
• Point of Contact: [More info needed]

Dataset Summary

[More Information Needed]

Supported Tasks and Leaderboards

[More Information Needed]

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&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

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

[More Information Needed]

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{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}
}