Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-label-classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
License:
metadata
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-label-classification
paperswithcode_id: dailydialog
pretty_name: DailyDialog
tags:
- emotion-classification
- dialog-act-classification
dataset_info:
features:
- name: dialog
sequence: string
- name: act
sequence:
class_label:
names:
'0': __dummy__
'1': inform
'2': question
'3': directive
'4': commissive
- name: emotion
sequence:
class_label:
names:
'0': no emotion
'1': anger
'2': disgust
'3': fear
'4': happiness
'5': sadness
'6': surprise
splits:
- name: train
num_bytes: 7296715
num_examples: 11118
- name: test
num_bytes: 655844
num_examples: 1000
- name: validation
num_bytes: 673943
num_examples: 1000
download_size: 4475921
dataset_size: 8626502
Dataset Card for "daily_dialog"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: http://yanran.li/dailydialog
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 4.48 MB
- Size of the generated dataset: 8.63 MB
- Total amount of disk used: 13.11 MB
Dataset Summary
We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects. The language is human-written and less noisy. The dialogues in the dataset reflect our daily communication way and cover various topics about our daily life. We also manually label the developed dataset with communication intention and emotion information. Then, we evaluate existing approaches on DailyDialog dataset and hope it benefit the research field of dialog systems.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
default
- Size of downloaded dataset files: 4.48 MB
- Size of the generated dataset: 8.63 MB
- Total amount of disk used: 13.11 MB
An example of 'validation' looks as follows.
This example was too long and was cropped:
{
"act": [2, 1, 1, 1, 1, 2, 3, 2, 3, 4],
"dialog": "[\"Good afternoon . This is Michelle Li speaking , calling on behalf of IBA . Is Mr Meng available at all ? \", \" This is Mr Meng ...",
"emotion": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
}
Data Fields
The data fields are the same among all splits.
default
dialog: alistofstringfeatures.act: alistof classification labels, with possible values including__dummy__(0),inform(1),question(2),directive(3) andcommissive(4).emotion: alistof classification labels, with possible values includingno emotion(0),anger(1),disgust(2),fear(3),happiness(4),sadness(5) andsurprise(6).
Data Splits
| name | train | validation | test |
|---|---|---|---|
| default | 11118 | 1000 | 1000 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Dataset provided for research purposes only. Please check dataset license for additional information.
Additional Information
Dataset Curators
Licensing Information
DailyDialog dataset is licensed under CC BY-NC-SA 4.0.
Citation Information
@InProceedings{li2017dailydialog,
author = {Li, Yanran and Su, Hui and Shen, Xiaoyu and Li, Wenjie and Cao, Ziqiang and Niu, Shuzi},
title = {DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset},
booktitle = {Proceedings of The 8th International Joint Conference on Natural Language Processing (IJCNLP 2017)},
year = {2017}
}