Datasets:
Tasks:
Question Answering
Languages:
English
Size:
10K<n<100K
ArXiv:
Tags:
table-question-answering
License:
albertvillanova
HF staff
Convert dataset sizes from base 2 to base 10 in the dataset card (#2)
d39cd16
annotations_creators: | |
- crowdsourced | |
language_creators: | |
- found | |
language: | |
- en | |
license: | |
- cc-by-4.0 | |
multilinguality: | |
- monolingual | |
paperswithcode_id: null | |
pretty_name: WikiTableQuestions | |
size_categories: | |
- 10K<n<100K | |
source_datasets: | |
- original | |
task_categories: | |
- question-answering | |
task_ids: [] | |
tags: | |
- table-question-answering | |
dataset_info: | |
- config_name: random-split-1 | |
features: | |
- name: id | |
dtype: string | |
- name: question | |
dtype: string | |
- name: answers | |
sequence: string | |
- name: table | |
struct: | |
- name: header | |
sequence: string | |
- name: rows | |
sequence: | |
sequence: string | |
- name: name | |
dtype: string | |
splits: | |
- name: train | |
num_bytes: 30364389 | |
num_examples: 11321 | |
- name: test | |
num_bytes: 11423506 | |
num_examples: 4344 | |
- name: validation | |
num_bytes: 7145768 | |
num_examples: 2831 | |
download_size: 29267445 | |
dataset_size: 48933663 | |
- config_name: random-split-2 | |
features: | |
- name: id | |
dtype: string | |
- name: question | |
dtype: string | |
- name: answers | |
sequence: string | |
- name: table | |
struct: | |
- name: header | |
sequence: string | |
- name: rows | |
sequence: | |
sequence: string | |
- name: name | |
dtype: string | |
splits: | |
- name: train | |
num_bytes: 30098954 | |
num_examples: 11314 | |
- name: test | |
num_bytes: 11423506 | |
num_examples: 4344 | |
- name: validation | |
num_bytes: 7411203 | |
num_examples: 2838 | |
download_size: 29267445 | |
dataset_size: 48933663 | |
- config_name: random-split-3 | |
features: | |
- name: id | |
dtype: string | |
- name: question | |
dtype: string | |
- name: answers | |
sequence: string | |
- name: table | |
struct: | |
- name: header | |
sequence: string | |
- name: rows | |
sequence: | |
sequence: string | |
- name: name | |
dtype: string | |
splits: | |
- name: train | |
num_bytes: 28778697 | |
num_examples: 11314 | |
- name: test | |
num_bytes: 11423506 | |
num_examples: 4344 | |
- name: validation | |
num_bytes: 8731460 | |
num_examples: 2838 | |
download_size: 29267445 | |
dataset_size: 48933663 | |
- config_name: random-split-4 | |
features: | |
- name: id | |
dtype: string | |
- name: question | |
dtype: string | |
- name: answers | |
sequence: string | |
- name: table | |
struct: | |
- name: header | |
sequence: string | |
- name: rows | |
sequence: | |
sequence: string | |
- name: name | |
dtype: string | |
splits: | |
- name: train | |
num_bytes: 30166421 | |
num_examples: 11321 | |
- name: test | |
num_bytes: 11423506 | |
num_examples: 4344 | |
- name: validation | |
num_bytes: 7343736 | |
num_examples: 2831 | |
download_size: 29267445 | |
dataset_size: 48933663 | |
- config_name: random-split-5 | |
features: | |
- name: id | |
dtype: string | |
- name: question | |
dtype: string | |
- name: answers | |
sequence: string | |
- name: table | |
struct: | |
- name: header | |
sequence: string | |
- name: rows | |
sequence: | |
sequence: string | |
- name: name | |
dtype: string | |
splits: | |
- name: train | |
num_bytes: 30333964 | |
num_examples: 11316 | |
- name: test | |
num_bytes: 11423506 | |
num_examples: 4344 | |
- name: validation | |
num_bytes: 7176193 | |
num_examples: 2836 | |
download_size: 29267445 | |
dataset_size: 48933663 | |
# Dataset Card for WikiTableQuestions | |
## Table of Contents | |
- [Dataset Description](#dataset-description) | |
- [Dataset Summary](#dataset-summary) | |
- [Supported Tasks](#supported-tasks-and-leaderboards) | |
- [Languages](#languages) | |
- [Dataset Structure](#dataset-structure) | |
- [Data Instances](#data-instances) | |
- [Data Fields](#data-instances) | |
- [Data Splits](#data-instances) | |
- [Dataset Creation](#dataset-creation) | |
- [Curation Rationale](#curation-rationale) | |
- [Source Data](#source-data) | |
- [Annotations](#annotations) | |
- [Personal and Sensitive Information](#personal-and-sensitive-information) | |
- [Considerations for Using the Data](#considerations-for-using-the-data) | |
- [Social Impact of Dataset](#social-impact-of-dataset) | |
- [Discussion of Biases](#discussion-of-biases) | |
- [Other Known Limitations](#other-known-limitations) | |
- [Additional Information](#additional-information) | |
- [Dataset Curators](#dataset-curators) | |
- [Licensing Information](#licensing-information) | |
- [Citation Information](#citation-information) | |
## Dataset Description | |
- **Homepage:** [WikiTableQuestions homepage](https://nlp.stanford.edu/software/sempre/wikitable) | |
- **Repository:** [WikiTableQuestions repository](https://github.com/ppasupat/WikiTableQuestions) | |
- **Paper:** [Compositional Semantic Parsing on Semi-Structured Tables](https://arxiv.org/abs/1508.00305) | |
- **Leaderboard:** [WikiTableQuestions leaderboard on PaperWithCode](https://paperswithcode.com/dataset/wikitablequestions) | |
- **Point of Contact:** [Needs More Information] | |
### Dataset Summary | |
The WikiTableQuestions dataset is a large-scale dataset for the task of question answering on semi-structured tables. | |
### Supported Tasks and Leaderboards | |
question-answering, table-question-answering | |
### Languages | |
en | |
## Dataset Structure | |
### Data Instances | |
#### default | |
- **Size of downloaded dataset files:** 29.27 MB | |
- **Size of the generated dataset:** 47.90 MB | |
- **Total amount of disk used:** 77.18 MB | |
An example of 'validation' looks as follows: | |
``` | |
{ | |
"id": "nt-0", | |
"question": "what was the last year where this team was a part of the usl a-league?", | |
"answers": ["2004"], | |
"table": { | |
"header": ["Year", "Division", "League", ...], | |
"name": "csv/204-csv/590.csv", | |
"rows": [ | |
["2001", "2", "USL A-League", ...], | |
["2002", "2", "USL A-League", ...], | |
... | |
] | |
} | |
} | |
``` | |
### Data Fields | |
The data fields are the same among all splits. | |
#### default | |
- `id`: a `string` feature. | |
- `question`: a `string` feature. | |
- `answers`: a `list` of `string` feature. | |
- `table`: a dictionary feature containing: | |
- `header`: a `list` of `string` features. | |
- `rows`: a `list` of `list` of `string` features: | |
- `name`: a `string` feature. | |
### Data Splits | |
| name |train|validation|test | | |
|-------|----:|---------:|----:| | |
|default|11321| 2831|4344| | |
## Dataset Creation | |
### Curation Rationale | |
[Needs More Information] | |
### Source Data | |
#### Initial Data Collection and Normalization | |
[Needs More Information] | |
#### Who are the source language producers? | |
[Needs More Information] | |
### Annotations | |
#### Annotation process | |
[Needs More Information] | |
#### Who are the annotators? | |
[Needs More Information] | |
### Personal and Sensitive Information | |
[Needs More Information] | |
## Considerations for Using the Data | |
### Social Impact of Dataset | |
[Needs More Information] | |
### Discussion of Biases | |
[Needs More Information] | |
### Other Known Limitations | |
[Needs More Information] | |
## Additional Information | |
### Dataset Curators | |
Panupong Pasupat and Percy Liang | |
### Licensing Information | |
Creative Commons Attribution Share Alike 4.0 International | |
### Citation Information | |
``` | |
@inproceedings{pasupat-liang-2015-compositional, | |
title = "Compositional Semantic Parsing on Semi-Structured Tables", | |
author = "Pasupat, Panupong and Liang, Percy", | |
booktitle = "Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)", | |
month = jul, | |
year = "2015", | |
address = "Beijing, China", | |
publisher = "Association for Computational Linguistics", | |
url = "https://aclanthology.org/P15-1142", | |
doi = "10.3115/v1/P15-1142", | |
pages = "1470--1480", | |
} | |
``` | |
### Contributions | |
Thanks to [@SivilTaram](https://github.com/SivilTaram) for adding this dataset. |