Datasets:
metadata
pretty_name: SEA Abstractive Summarization
license:
- cc-by-nc-sa-4.0
task_categories:
- text-generation
language:
- id
- ta
- th
- vi
dataset_info:
- config_name: id
features:
- name: id
dtype: string
- name: label
dtype: string
- name: prompts
list:
- name: text
dtype: string
- name: metadata
struct:
- name: language
dtype: string
- name: title
dtype: string
- name: url
dtype: string
splits:
- name: eval
num_bytes: 295312
num_examples: 100
- name: examples
num_bytes: 6660
num_examples: 5
download_size: 189280
dataset_size: 301972
- config_name: my
features:
- name: id
dtype: string
- name: label
dtype: string
- name: prompts
list:
- name: text
dtype: string
- name: metadata
struct:
- name: language
dtype: string
- name: title
dtype: string
splits:
- name: eval
num_bytes: 791430
num_examples: 100
- name: examples
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num_examples: 5
download_size: 288156
dataset_size: 854800
- config_name: ta
features:
- name: id
dtype: string
- name: label
dtype: string
- name: prompts
list:
- name: text
dtype: string
- name: metadata
struct:
- name: language
dtype: string
- name: title
dtype: string
- name: url
dtype: string
splits:
- name: eval
num_bytes: 1011914
num_examples: 100
- name: examples
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num_examples: 5
download_size: 371811
dataset_size: 1023261
- config_name: th
features:
- name: id
dtype: string
- name: label
dtype: string
- name: prompts
list:
- name: text
dtype: string
- name: metadata
struct:
- name: language
dtype: string
- name: title
dtype: string
- name: url
dtype: string
splits:
- name: eval
num_bytes: 1148394
num_examples: 100
- name: examples
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num_examples: 5
download_size: 455457
dataset_size: 1158121
- config_name: tl
features:
- name: id
dtype: string
- name: label
dtype: string
- name: prompts
list:
- name: text
dtype: string
- name: metadata
struct:
- name: language
dtype: string
- name: title
dtype: string
- name: url
dtype: string
splits:
- name: eval
num_bytes: 89405
num_examples: 100
- name: examples
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num_examples: 5
download_size: 67523
dataset_size: 93564
- config_name: vi
features:
- name: id
dtype: string
- name: label
dtype: string
- name: prompts
list:
- name: text
dtype: string
- name: metadata
struct:
- name: language
dtype: string
- name: title
dtype: string
- name: url
dtype: string
splits:
- name: eval
num_bytes: 368697
num_examples: 100
- name: examples
num_bytes: 9736
num_examples: 5
download_size: 226848
dataset_size: 378433
configs:
- config_name: id
data_files:
- split: eval
path: id/eval-*
- split: examples
path: id/examples-*
- config_name: my
data_files:
- split: eval
path: my/eval-*
- split: examples
path: my/examples-*
- config_name: ta
data_files:
- split: eval
path: ta/eval-*
- split: examples
path: ta/examples-*
- config_name: th
data_files:
- split: eval
path: th/eval-*
- split: examples
path: th/examples-*
- config_name: tl
data_files:
- split: eval
path: tl/eval-*
- split: examples
path: tl/examples-*
- config_name: vi
data_files:
- split: eval
path: vi/eval-*
- split: examples
path: vi/examples-*
size_categories:
- n<1K
SEA Abstractive Summarization
SEA Abstractive Summarization evaluates a model's ability to read a document, identify the key points within, and summarize them into a coherent and fluent text while paraphrasing the document. It is sampled from XL-Sum for Indonesian, Tamil, Thai, and Vietnamese.
Supported Tasks and Leaderboards
SEA Abstractive Summarization is designed for evaluating chat or instruction-tuned large language models (LLMs). It is part of the SEA-HELM leaderboard from AI Singapore.
Languages
- Indonesian (id)
- Tamil (ta)
- Thai (th)
- Vietnamese (vi)
Dataset Details
SEA Abstractive Summarization is split by language, with additional splits containing fewshot examples. Below are the statistics for this dataset. The number of tokens only refer to the strings of text found within the prompts column.
| Split | # of examples | # of GPT-4o tokens | # of Gemma 2 tokens | # of Llama 3 tokens |
|---|---|---|---|---|
| id | 100 | 61628 | 55485 | 77016 |
| ta | 100 | 114275 | 156476 | 457559 |
| th | 100 | 155203 | 151988 | 176985 |
| vi | 100 | 86305 | 78285 | 82269 |
| id_fewshot | 5 | 1124 | 1050 | 1430 |
| ta_fewshot | 5 | 964 | 1339 | 3905 |
| th_fewshot | 5 | 925 | 869 | 1062 |
| vi_fewshot | 5 | 2396 | 2170 | 2282 |
| total | 420 | 422820 | 447662 | 802508 |
Data Sources
| Data Source | License | Language/s | Split/s |
|---|---|---|---|
| XL-Sum | CC BY-NC-SA 4.0 | Indonesian, Tamil, Thai, Vietnamese | id, id_fewshot, ta, ta_fewshot, th, th_fewshot, vi, vi_fewshot |
License
For the license/s of the dataset/s, please refer to the data sources table above.
We endeavor to ensure data used is permissible and have chosen datasets from creators who have processes to exclude copyrighted or disputed data.
Acknowledgement
This project is supported by the National Research Foundation Singapore and Infocomm Media Development Authority (IMDA), Singapore under its National Large Language Model Funding Initiative.
References
@inproceedings{hasan-etal-2021-xl,
title = "{XL}-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages",
author = "Hasan, Tahmid and
Bhattacharjee, Abhik and
Islam, Md. Saiful and
Mubasshir, Kazi and
Li, Yuan-Fang and
Kang, Yong-Bin and
Rahman, M. Sohel and
Shahriyar, Rifat",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-acl.413",
pages = "4693--4703",
}
@misc{leong2023bhasaholisticsoutheastasian,
title={BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models},
author={Wei Qi Leong and Jian Gang Ngui and Yosephine Susanto and Hamsawardhini Rengarajan and Kengatharaiyer Sarveswaran and William Chandra Tjhi},
year={2023},
eprint={2309.06085},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2309.06085},
}