This dataset only consists of linearized underlying data table of charts and their corresponding summaries. 

Model that use this dataset: https://huggingface.co/saadob12/t5_C2T_autochart

## Created By: 
Zhu, J., Ran, J., Lee, R. K. W., Choo, K., & Li, Z. (2021). AutoChart: A Dataset for Chart-to-Text Generation Task. arXiv preprint arXiv:2108.06897.

**Paper**: https://arxiv.org/abs/2108.06897 

**Orignal gitlab repo**: https://gitlab.com/bottle_shop/snlg/chart/autochart

# Description from the original gitlab repo

Analytical description of charts is an exciting and important research area with many academia and industry benefits. Yet, this challenging task has received limited attention from the computational linguistics research community. This paper aims to encourage more research into this important area by proposing AutoChart, the first large chart analytical description dataset. Specifically, we offer a novel framework that generates the charts and their analytical description automatically. We also empirically demonstrate that the generate analytical descriptions are diverse, coherent, and relevant to the corresponding charts. The image file can be downloaded in [this link](https://drive.google.com/file/d/1SgVqyDnZypO3nSqHAG6aXHal-o-F60EC/view?usp=sharing).


# Langugage

The data is in english and the summaries are in english. 

# Dataset split
| train | valid  | test |
|:---:|:---:| :---:|
| 23336  | 1297  | 1296 |


**Name of Contributor:** Saad Obaid ul Islam 

arxiv:2108.06897 region:us
{}
TAGS
#arxiv-2108.06897 #region-us 

This dataset only consists of linearized underlying data table of charts and their corresponding summaries.


Model that use this dataset: URL


Created By:
-----------


Zhu, J., Ran, J., Lee, R. K. W., Choo, K., & Li, Z. (2021). AutoChart: A Dataset for Chart-to-Text Generation Task. arXiv preprint arXiv:2108.06897.


Paper: URL


Orignal gitlab repo: URL


Description from the original gitlab repo
=========================================


Analytical description of charts is an exciting and important research area with many academia and industry benefits. Yet, this challenging task has received limited attention from the computational linguistics research community. This paper aims to encourage more research into this important area by proposing AutoChart, the first large chart analytical description dataset. Specifically, we offer a novel framework that generates the charts and their analytical description automatically. We also empirically demonstrate that the generate analytical descriptions are diverse, coherent, and relevant to the corresponding charts. The image file can be downloaded in this link.


Langugage
=========


The data is in english and the summaries are in english.


Dataset split
=============



Name of Contributor: Saad Obaid ul Islam



TAGS
#arxiv-2108.06897 #region-us 

passage: TAGS
#arxiv-2108.06897 #region-us 
