Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Sub-tasks:
open-domain-qa
Languages:
Polish
Size:
1K - 10K
License:
metadata
annotations_creators:
- expert-generated
language_creators:
- other
language:
- pl
license:
- bsd-3-clause
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
pretty_name: dyk
dataset_info:
features:
- name: q_id
dtype: string
- name: question
dtype: string
- name: answer
dtype: string
- name: target
dtype:
class_label:
names:
'0': '0'
'1': '1'
splits:
- name: train
num_bytes: 1388678
num_examples: 4154
- name: test
num_bytes: 353631
num_examples: 1029
download_size: 1125972
dataset_size: 1742309
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
Dataset Card for [Dataset Name]
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: http://nlp.pwr.wroc.pl/en/tools-and-resources/resources/czy-wiesz-question-answering-dataset
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:
Dataset Summary
The Did You Know (pol. Czy wiesz?) dataset consists of human-annotated question-answer pairs. The task is to predict if the answer is correct. We chose the negatives which have the largest token overlap with a question.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
Polish
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
- q_id: question id
- question: question sentence
- answer: answer sentence
- target: 1 if the answer is correct, 0 otherwise. Note that the test split doesn't have target values so -1 is used instead
Data Splits
[More Information Needed]
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?
[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
CC BY-SA 3.0
Citation Information
[More Information Needed]
Contributions
Thanks to @abecadel for adding this dataset.