Datasets:
Tasks:
Question Answering
Formats:
parquet
Sub-tasks:
multiple-choice-qa
Languages:
English
Size:
10K - 100K
ArXiv:
License:
metadata
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
paperswithcode_id: codah
pretty_name: COmmonsense Dataset Adversarially-authored by Humans
dataset_info:
- config_name: codah
features:
- name: id
dtype: int32
- name: question_category
dtype:
class_label:
names:
'0': Idioms
'1': Reference
'2': Polysemy
'3': Negation
'4': Quantitative
'5': Others
- name: question_propmt
dtype: string
- name: candidate_answers
sequence: string
- name: correct_answer_idx
dtype: int32
splits:
- name: train
num_bytes: 571196
num_examples: 2776
download_size: 352902
dataset_size: 571196
- config_name: fold_0
features:
- name: id
dtype: int32
- name: question_category
dtype:
class_label:
names:
'0': Idioms
'1': Reference
'2': Polysemy
'3': Negation
'4': Quantitative
'5': Others
- name: question_propmt
dtype: string
- name: candidate_answers
sequence: string
- name: correct_answer_idx
dtype: int32
splits:
- name: train
num_bytes: 344900
num_examples: 1665
- name: validation
num_bytes: 114199
num_examples: 556
- name: test
num_bytes: 112097
num_examples: 555
download_size: 379179
dataset_size: 571196
- config_name: fold_1
features:
- name: id
dtype: int32
- name: question_category
dtype:
class_label:
names:
'0': Idioms
'1': Reference
'2': Polysemy
'3': Negation
'4': Quantitative
'5': Others
- name: question_propmt
dtype: string
- name: candidate_answers
sequence: string
- name: correct_answer_idx
dtype: int32
splits:
- name: train
num_bytes: 340978
num_examples: 1665
- name: validation
num_bytes: 114199
num_examples: 556
- name: test
num_bytes: 116019
num_examples: 555
download_size: 379728
dataset_size: 571196
- config_name: fold_2
features:
- name: id
dtype: int32
- name: question_category
dtype:
class_label:
names:
'0': Idioms
'1': Reference
'2': Polysemy
'3': Negation
'4': Quantitative
'5': Others
- name: question_propmt
dtype: string
- name: candidate_answers
sequence: string
- name: correct_answer_idx
dtype: int32
splits:
- name: train
num_bytes: 342281
num_examples: 1665
- name: validation
num_bytes: 114199
num_examples: 556
- name: test
num_bytes: 114716
num_examples: 555
download_size: 379126
dataset_size: 571196
- config_name: fold_3
features:
- name: id
dtype: int32
- name: question_category
dtype:
class_label:
names:
'0': Idioms
'1': Reference
'2': Polysemy
'3': Negation
'4': Quantitative
'5': Others
- name: question_propmt
dtype: string
- name: candidate_answers
sequence: string
- name: correct_answer_idx
dtype: int32
splits:
- name: train
num_bytes: 342832
num_examples: 1665
- name: validation
num_bytes: 114199
num_examples: 556
- name: test
num_bytes: 114165
num_examples: 555
download_size: 379178
dataset_size: 571196
- config_name: fold_4
features:
- name: id
dtype: int32
- name: question_category
dtype:
class_label:
names:
'0': Idioms
'1': Reference
'2': Polysemy
'3': Negation
'4': Quantitative
'5': Others
- name: question_propmt
dtype: string
- name: candidate_answers
sequence: string
- name: correct_answer_idx
dtype: int32
splits:
- name: train
num_bytes: 342844
num_examples: 1665
- name: validation
num_bytes: 114177
num_examples: 555
- name: test
num_bytes: 114211
num_examples: 556
download_size: 485130
dataset_size: 571232
configs:
- config_name: codah
data_files:
- split: train
path: codah/train-*
- config_name: fold_0
data_files:
- split: train
path: fold_0/train-*
- split: validation
path: fold_0/validation-*
- split: test
path: fold_0/test-*
- config_name: fold_1
data_files:
- split: train
path: fold_1/train-*
- split: validation
path: fold_1/validation-*
- split: test
path: fold_1/test-*
- config_name: fold_2
data_files:
- split: train
path: fold_2/train-*
- split: validation
path: fold_2/validation-*
- split: test
path: fold_2/test-*
- config_name: fold_3
data_files:
- split: train
path: fold_3/train-*
- split: validation
path: fold_3/validation-*
- split: test
path: fold_3/test-*
Dataset Card for COmmonsense Dataset Adversarially-authored by Humans
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: Add homepage URL here if available (unless it's a GitHub repository)
- Repository: If the dataset is hosted on github or has a github homepage, add URL here
- Paper: If the dataset was introduced by a paper or there was a paper written describing the dataset, add URL here (landing page for Arxiv paper preferred)
- Leaderboard: If the dataset supports an active leaderboard, add link here
- Point of Contact: If known, name and email of at least one person the reader can contact for questions about the dataset.
Dataset Summary
[More Information Needed]
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
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
[More Information Needed]
Contributions
Thanks to @patil-suraj for adding this dataset.