File size: 4,490 Bytes
43d46be 17d811d 43d46be 17d811d a3bda6f 43d46be f15212d e441ce3 4089584 43d46be e441ce3 43d46be e441ce3 43d46be 388bd3c 43d46be da94279 43d46be 388bd3c 4089584 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 |
---
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 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.
|