|
--- |
|
annotations_creators: |
|
- expert-generated |
|
- crowdsourced |
|
language: |
|
- en |
|
language_creators: |
|
- found |
|
- crowdsourced |
|
- expert-generated |
|
license: |
|
- c-uda |
|
multilinguality: |
|
- monolingual |
|
paperswithcode_id: totto |
|
pretty_name: HiTab |
|
size_categories: |
|
- 10K<n<100K |
|
source_datasets: |
|
- original |
|
- extended|totto |
|
tags: [] |
|
task_categories: |
|
- table-to-text |
|
- question-answering |
|
task_ids: [] |
|
dataset_info: |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: table_id |
|
dtype: string |
|
- name: table_source |
|
dtype: string |
|
- name: sentence_id |
|
dtype: string |
|
- name: sub_sentence_id |
|
dtype: string |
|
- name: sub_sentence |
|
dtype: string |
|
- name: question |
|
dtype: string |
|
- name: answer |
|
dtype: large_string |
|
- name: aggregation |
|
dtype: large_string |
|
- name: linked_cells |
|
dtype: large_string |
|
- name: answer_formulas |
|
dtype: large_string |
|
- name: reference_cells_map |
|
dtype: large_string |
|
- name: table_content |
|
dtype: large_string |
|
splits: |
|
- name: train |
|
num_bytes: 36419103 |
|
num_examples: 7417 |
|
- name: validation |
|
num_bytes: 8312699 |
|
num_examples: 1671 |
|
- name: test |
|
num_bytes: 7710891 |
|
num_examples: 1584 |
|
download_size: 6462957 |
|
dataset_size: 52442693 |
|
--- |
|
|
|
# Dataset Card for HiTab |
|
|
|
## Dataset Description |
|
- **Homepage:** https://www.microsoft.com/en-us/research/publication/hitab-a-hierarchical-table-dataset-for-question-answering-and-natural-language-generation/ |
|
- **Repository:** https://github.com/microsoft/HiTab/blob/main/LICENSE |
|
- **Paper:** https://aclanthology.org/2022.acl-long.78/ |
|
|
|
### Dataset Summary |
|
HiTab is a dataset for question answering and data-to-text over hierarchical tables . It contains 10,672 samples and 3,597 tables from statistical reports (StatCan, NSF) and Wikipedia (ToTTo). 98.1% of the tables in HiTab are with hierarchies. |
|
|
|
### Supported Tasks and Leaderboards |
|
Table-to-Text Generation, Question Answering |
|
|
|
### Languages |
|
English |
|
|
|
### Data Instances |
|
3,597 tables, 10,686 sentences |
|
|
|
### Data Splits |
|
train, test, validation |
|
|
|
## Dataset Creation |
|
During the dataset annotation process, annotators first manually collect tables and descriptive sentences highly-related to tables on statistical websites written by professional analysts. Then these descriptions are revised to questions to preserve the original meanings and analyses. |
|
|
|
### Licensing Information |
|
|
|
This dataset follows the Computational Use of Data Agreement v1.0. |
|
|
|
### Citation Information |
|
|
|
``` |
|
@article{cheng2021hitab, |
|
title={HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation}, |
|
author={Cheng, Zhoujun and Dong, Haoyu and Wang, Zhiruo and Jia, Ran and Guo, Jiaqi and Gao, Yan and Han, Shi and Lou, Jian-Guang and Zhang, Dongmei}, |
|
journal={arXiv preprint arXiv:2108.06712}, |
|
year={2021} |
|
} |
