Datasets:

nikhilweee
/

sharc_modified

	---
	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&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.