Datasets:

Sub-tasks:
extractive-qa
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Annotations Creators:
crowdsourced
Source Datasets:
extended|sharc
ArXiv:
License:
sharc_modified / README.md
system's picture
system HF staff
Update files from the datasets library (from 1.7.0)
62239a3
---
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
paperswithcode_id: null
---
# Dataset Card Creation Guide
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** [More info needed]
- **Repository:** [github](https://github.com/nikhilweee/neural-conv-qa)
- **Paper:** [Neural Conversational QA: Learning to Reason v.s. Exploiting Patterns](https://arxiv.org/abs/1909.03759)
- **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&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
[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}
}
```
### Contributions
Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset.