Datasets:
deal_or_no_dialog

	---
	annotations_creators:
	- crowdsourced
	language_creators:
	- crowdsourced
	language:
	- en
	license:
	- cc-by-4.0
	multilinguality:
	- monolingual
	size_categories:
	- 10K<n<100K
	source_datasets:
	- original
	task_categories:
	- conversational
	task_ids: []
	paperswithcode_id: negotiation-dialogues-dataset
	pretty_name: Deal or No Deal Negotiator
	dataset_info:
	- config_name: dialogues
	features:
	- name: input
	sequence:
	- name: count
	dtype: int32
	- name: value
	dtype: int32
	- name: dialogue
	dtype: string
	- name: output
	dtype: string
	- name: partner_input
	sequence:
	- name: count
	dtype: int32
	- name: value
	dtype: int32
	splits:
	- name: train
	num_bytes: 3860624
	num_examples: 10095
	- name: test
	num_bytes: 396258
	num_examples: 1052
	- name: validation
	num_bytes: 418491
	num_examples: 1087
	download_size: 5239072
	dataset_size: 4675373
	- config_name: self_play
	features:
	- name: input
	sequence:
	- name: count
	dtype: int32
	- name: value
	dtype: int32
	splits:
	- name: train
	num_bytes: 261512
	num_examples: 8172
	download_size: 98304
	dataset_size: 261512
	---


	# Dataset Card for Deal or No Deal Negotiator

	## 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

	- Repository: [Dataset Repository](https://github.com/facebookresearch/end-to-end-negotiator)
	- Paper: [Deal or No Deal? End-to-End Learning for Negotiation Dialogues](https://arxiv.org/abs/1706.05125)

	### Dataset Summary

	A large dataset of human-human negotiations on a multi-issue bargaining task, where agents who cannot observe each other’s reward functions must reach an agreement (or a deal) via natural language dialogue.

	### Supported Tasks and Leaderboards

	Train end-to-end models for negotiation

	### Languages

	The text in the dataset is in English

	## Dataset Structure

	### Data Instances

	{'dialogue': 'YOU: i love basketball and reading <eos> THEM: no . i want the hat and the balls <eos> YOU: both balls ? <eos> THEM: yeah or 1 ball and 1 book <eos> YOU: ok i want the hat and you can have the rest <eos> THEM: okay deal ill take the books and the balls you can have only the hat <eos> YOU: ok <eos> THEM: <selection>',
	'input': {'count': [3, 1, 2], 'value': [0, 8, 1]},
	'output': 'item0=0 item1=1 item2=0 item0=3 item1=0 item2=2',
	'partner_input': {'count': [3, 1, 2], 'value': [1, 3, 2]}}

	### Data Fields

	`dialogue`: The dialogue between the agents. \
	`input`: The input of the firt agent. \
	`partner_input`: The input of the other agent. \
	`count`: The count of the three available items. \
	`value`: The value of the three available items. \
	`output`: Describes how many of each of the three item typesare assigned to each agent


	### Data Splits

	\| \| train \| validation \| test \|
	\|------------\|------:\|-----------:\|-----:\|
	\| dialogues \| 10095 \| 1087 \| 1052 \|
	\| self_play \| 8172 \| NA \| NA \|

	## Dataset Creation

	### Curation Rationale

	[More Information Needed]

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed]

	#### Who are the source language producers?

	[More Information Needed]

	### Annotations

	#### Annotation process

	[More Information Needed]

	#### Who are the annotators?

	Human workers using Amazon Mechanical Turk. They were paid $0.15 per dialogue, with a $0.05 bonus for maximal scores. Only workers based in the United States with a 95% approval rating and at least 5000 previous HITs were used.

	### 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

	The project is licenced under CC-by-NC

	### Citation Information
	```
	@article{lewis2017deal,
	title={Deal or no deal? end-to-end learning for negotiation dialogues},
	author={Lewis, Mike and Yarats, Denis and Dauphin, Yann N and Parikh, Devi and Batra, Dhruv},
	journal={arXiv preprint arXiv:1706.05125},
	year={2017}
	}
	```

	### Contributions

	Thanks to [@moussaKam](https://github.com/moussaKam) for adding this dataset.