metadata
annotations_creators:
- crowdsourced
language_creators:
- other
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<200K
source_datasets:
- extended|other
task_categories:
- text-classification
task_ids:
- natural-language-inference
- sentiment-analysis
- hate-speech-detection
paperswithcode_id: placeholder
pretty_name: TID-8
tags:
- tid8
- annotation disagreement
dataset_info:
- config_name: commitmentbank-ann
features:
- name: HitID
dtype: string
- name: Verb
dtype: string
- name: Context
dtype: string
- name: Prompt
dtype: string
- name: Target
dtype: string
- name: ModalType
dtype: string
- name: Embedding
dtype: string
- name: MatTense
dtype: string
- name: weak_labels
sequence: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': '0'
'1': '1'
'2': '2'
'3': '3'
'4': '-3'
'5': '-1'
'6': '-2'
splits:
- name: train
num_bytes: 7153364
num_examples: 7816
- name: test
num_bytes: 3353745
num_examples: 3729
download_size: 3278616
dataset_size: 10507109
- config_name: commitmentbank-atr
features:
- name: HitID
dtype: string
- name: Verb
dtype: string
- name: Context
dtype: string
- name: Prompt
dtype: string
- name: Target
dtype: string
- name: ModalType
dtype: string
- name: Embedding
dtype: string
- name: MatTense
dtype: string
- name: weak_labels
sequence: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': '0'
'1': '1'
'2': '2'
'3': '3'
'4': '-3'
'5': '-1'
'6': '-2'
splits:
- name: train
num_bytes: 6636145
num_examples: 7274
- name: test
num_bytes: 3870964
num_examples: 4271
download_size: 3301698
dataset_size: 10507109
- config_name: friends_qia-ann
features:
- name: Season
dtype: string
- name: Episode
dtype: string
- name: Category
dtype: string
- name: Q_person
dtype: string
- name: A_person
dtype: string
- name: Q_original
dtype: string
- name: Q_modified
dtype: string
- name: A_modified
dtype: string
- name: Annotation_1
dtype: string
- name: Annotation_2
dtype: string
- name: Annotation_3
dtype: string
- name: Goldstandard
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': '1'
'1': '2'
'2': '3'
'3': '4'
'4': '5'
splits:
- name: validation
num_bytes: 687135
num_examples: 1872
- name: train
num_bytes: 4870170
num_examples: 13113
- name: test
num_bytes: 693033
num_examples: 1872
download_size: 1456765
dataset_size: 6250338
- config_name: friends_qia-atr
features:
- name: Season
dtype: string
- name: Episode
dtype: string
- name: Category
dtype: string
- name: Q_person
dtype: string
- name: A_person
dtype: string
- name: Q_original
dtype: string
- name: Q_modified
dtype: string
- name: A_modified
dtype: string
- name: Annotation_1
dtype: string
- name: Annotation_2
dtype: string
- name: Annotation_3
dtype: string
- name: Goldstandard
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': '1'
'1': '2'
'2': '3'
'3': '4'
'4': '5'
splits:
- name: train
num_bytes: 4166892
num_examples: 11238
- name: test
num_bytes: 2083446
num_examples: 5619
download_size: 3445839
dataset_size: 6250338
- config_name: goemotions-ann
features:
- name: author
dtype: string
- name: subreddit
dtype: string
- name: link_id
dtype: string
- name: parent_id
dtype: string
- name: created_utc
dtype: string
- name: rater_id
dtype: string
- name: example_very_unclear
dtype: string
- name: admiration
dtype: string
- name: amusement
dtype: string
- name: anger
dtype: string
- name: annoyance
dtype: string
- name: approval
dtype: string
- name: caring
dtype: string
- name: confusion
dtype: string
- name: curiosity
dtype: string
- name: desire
dtype: string
- name: disappointment
dtype: string
- name: disapproval
dtype: string
- name: disgust
dtype: string
- name: embarrassment
dtype: string
- name: excitement
dtype: string
- name: fear
dtype: string
- name: gratitude
dtype: string
- name: grief
dtype: string
- name: joy
dtype: string
- name: love
dtype: string
- name: nervousness
dtype: string
- name: optimism
dtype: string
- name: pride
dtype: string
- name: realization
dtype: string
- name: relief
dtype: string
- name: remorse
dtype: string
- name: sadness
dtype: string
- name: surprise
dtype: string
- name: neutral
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': positive
'1': ambiguous
'2': negative
'3': neutral
splits:
- name: train
num_bytes: 46277072
num_examples: 135504
- name: test
num_bytes: 19831033
num_examples: 58129
download_size: 24217871
dataset_size: 66108105
- config_name: goemotions-atr
features:
- name: author
dtype: string
- name: subreddit
dtype: string
- name: link_id
dtype: string
- name: parent_id
dtype: string
- name: created_utc
dtype: string
- name: rater_id
dtype: string
- name: example_very_unclear
dtype: string
- name: admiration
dtype: string
- name: amusement
dtype: string
- name: anger
dtype: string
- name: annoyance
dtype: string
- name: approval
dtype: string
- name: caring
dtype: string
- name: confusion
dtype: string
- name: curiosity
dtype: string
- name: desire
dtype: string
- name: disappointment
dtype: string
- name: disapproval
dtype: string
- name: disgust
dtype: string
- name: embarrassment
dtype: string
- name: excitement
dtype: string
- name: fear
dtype: string
- name: gratitude
dtype: string
- name: grief
dtype: string
- name: joy
dtype: string
- name: love
dtype: string
- name: nervousness
dtype: string
- name: optimism
dtype: string
- name: pride
dtype: string
- name: realization
dtype: string
- name: relief
dtype: string
- name: remorse
dtype: string
- name: sadness
dtype: string
- name: surprise
dtype: string
- name: neutral
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': positive
'1': ambiguous
'2': negative
'3': neutral
splits:
- name: train
num_bytes: 44856233
num_examples: 131395
- name: test
num_bytes: 21251872
num_examples: 62238
download_size: 24228953
dataset_size: 66108105
- config_name: hs_brexit-ann
features:
- name: other annotations
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': hate_speech
'1': not_hate_speech
splits:
- name: train
num_bytes: 1039008
num_examples: 4704
- name: test
num_bytes: 222026
num_examples: 1008
download_size: 144072
dataset_size: 1261034
- config_name: hs_brexit-atr
features:
- name: other annotations
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': hate_speech
'1': not_hate_speech
splits:
- name: train
num_bytes: 986132
num_examples: 4480
- name: test
num_bytes: 495738
num_examples: 2240
download_size: 604516
dataset_size: 1481870
- config_name: humor-ann
features:
- name: text_a
dtype: string
- name: text_b
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': B
'1': X
'2': A
splits:
- name: train
num_bytes: 28524839
num_examples: 98735
- name: test
num_bytes: 12220621
num_examples: 42315
download_size: 24035118
dataset_size: 40745460
- config_name: humor-atr
features:
- name: text_a
dtype: string
- name: text_b
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': B
'1': X
'2': A
splits:
- name: train
num_bytes: 28161248
num_examples: 97410
- name: test
num_bytes: 12584212
num_examples: 43640
download_size: 24099282
dataset_size: 40745460
- config_name: md-agreement-ann
features:
- name: task
dtype: string
- name: original_id
dtype: string
- name: domain
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': offensive_speech
'1': not_offensive_speech
splits:
- name: train
num_bytes: 7794988
num_examples: 32960
- name: test
num_bytes: 2498445
num_examples: 10553
download_size: 1606671
dataset_size: 10293433
- config_name: md-agreement-atr
features:
- name: task
dtype: string
- name: original_id
dtype: string
- name: domain
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': offensive_speech
'1': not_offensive_speech
splits:
- name: train
num_bytes: 8777085
num_examples: 37077
- name: test
num_bytes: 3957021
num_examples: 16688
download_size: 5766114
dataset_size: 12734106
- config_name: pejorative-ann
features:
- name: pejor_word
dtype: string
- name: word_definition
dtype: string
- name: annotator-1
dtype: string
- name: annotator-2
dtype: string
- name: annotator-3
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': pejorative
'1': non-pejorative
'2': undecided
splits:
- name: train
num_bytes: 350734
num_examples: 1535
- name: test
num_bytes: 150894
num_examples: 659
download_size: 168346
dataset_size: 501628
- config_name: pejorative-atr
features:
- name: pejor_word
dtype: string
- name: word_definition
dtype: string
- name: annotator-1
dtype: string
- name: annotator-2
dtype: string
- name: annotator-3
dtype: string
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': pejorative
'1': non-pejorative
'2': undecided
splits:
- name: train
num_bytes: 254138
num_examples: 1112
- name: test
num_bytes: 247490
num_examples: 1082
download_size: 188229
dataset_size: 501628
- config_name: sentiment-ann
features:
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': Neutral
'1': Somewhat positive
'2': Very negative
'3': Somewhat negative
'4': Very positive
splits:
- name: train
num_bytes: 9350333
num_examples: 59235
- name: test
num_bytes: 235013
num_examples: 1419
download_size: 4906597
dataset_size: 9585346
- config_name: sentiment-atr
features:
- name: question
dtype: string
- name: uid
dtype: string
- name: id
dtype: int32
- name: annotator_id
dtype: string
- name: answer
dtype: string
- name: answer_label
dtype:
class_label:
names:
'0': Neutral
'1': Somewhat positive
'2': Very negative
'3': Somewhat negative
'4': Very positive
splits:
- name: train
num_bytes: 6712084
num_examples: 42439
- name: test
num_bytes: 2873262
num_examples: 18215
download_size: 4762021
dataset_size: 9585346
configs:
- config_name: commitmentbank-ann
data_files:
- split: train
path: commitmentbank-ann/train-*
- split: test
path: commitmentbank-ann/test-*
- config_name: commitmentbank-atr
data_files:
- split: train
path: commitmentbank-atr/train-*
- split: test
path: commitmentbank-atr/test-*
- config_name: friends_qia-ann
data_files:
- split: validation
path: friends_qia-ann/validation-*
- split: train
path: friends_qia-ann/train-*
- split: test
path: friends_qia-ann/test-*
- config_name: friends_qia-atr
data_files:
- split: train
path: friends_qia-atr/train-*
- split: test
path: friends_qia-atr/test-*
- config_name: goemotions-ann
data_files:
- split: train
path: goemotions-ann/train-*
- split: test
path: goemotions-ann/test-*
- config_name: goemotions-atr
data_files:
- split: train
path: goemotions-atr/train-*
- split: test
path: goemotions-atr/test-*
- config_name: hs_brexit-ann
data_files:
- split: train
path: hs_brexit-ann/train-*
- split: test
path: hs_brexit-ann/test-*
- config_name: hs_brexit-atr
data_files:
- split: train
path: hs_brexit-atr/train-*
- split: test
path: hs_brexit-atr/test-*
- config_name: humor-ann
data_files:
- split: train
path: humor-ann/train-*
- split: test
path: humor-ann/test-*
- config_name: humor-atr
data_files:
- split: train
path: humor-atr/train-*
- split: test
path: humor-atr/test-*
- config_name: md-agreement-ann
data_files:
- split: train
path: md-agreement-ann/train-*
- split: test
path: md-agreement-ann/test-*
- config_name: md-agreement-atr
data_files:
- split: train
path: md-agreement-atr/train-*
- split: test
path: md-agreement-atr/test-*
- config_name: pejorative-ann
data_files:
- split: train
path: pejorative-ann/train-*
- split: test
path: pejorative-ann/test-*
- config_name: pejorative-atr
data_files:
- split: train
path: pejorative-atr/train-*
- split: test
path: pejorative-atr/test-*
- config_name: sentiment-ann
data_files:
- split: train
path: sentiment-ann/train-*
- split: test
path: sentiment-ann/test-*
- config_name: sentiment-atr
data_files:
- split: train
path: sentiment-atr/train-*
- split: test
path: sentiment-atr/test-*
Dataset Card for "TID-8"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: placeholder
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
Dataset Summary
TID-8 is a new aggregated benchmark focused on the task of letting models learn from data that has inherent disagreement proposed in link at Findings of EMNLP 2023. In the paper, we focus on the inherent disagreement and let the model directly learn from data that has such disagreement.
We provide two split for TID-8.
Annotation Split
We split the annotations for each annotator into train and test set.
In other words, the same set of annotators appear in both train, (val), and test sets.
For datasets that have splits originally, we follow the original split and remove datapoints in test sets that are annotated by an annotator who is not in the training set.
For datasets that do not have splits originally, we split the data into train and test set for convenience, you may further split the train set into a train and val set.
Annotator Split
We split annotators into train and test set.
In other words, a different set of annotators would appear in train and test sets.
We split the data into train and test set for convenience, you may consider further splitting the train set into a train and val set for performance validation.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
Data Fields
The data fields are the same among all splits. See aforementioned information.
Data Splits
See aforementioned information.
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
Additional Information
Dataset Curators
Licensing Information
Citation Information
@inproceedings{deng2023tid8,
title={You Are What You Annotate: Towards Better Models through Annotator Representations},
author={Deng, Naihao and Liu, Siyang and Zhang, Frederick Xinliang and Wu, Winston and Wang, Lu and Mihalcea, Rada},
booktitle={Findings of EMNLP 2023},
year={2023}
}
Note that each TID-8 dataset has its own citation. Please see the source to
get the correct citation for each contained dataset.