| --- |
| license: mit |
| language: |
| - en |
| - ja |
| - ko |
| - si |
| - ta |
| pretty_name: M2DS |
| tags: |
| - multilingual summarisation |
| - multi-document summarisation |
| - dataset |
| - nlp |
| - bbc |
| task_categories: |
| - summarization |
| size_categories: |
| - 10K<n<100K |
| configs: |
| - config_name: english |
| default: true |
| data_files: |
| - split: train |
| path: english/train.json |
| - split: validation |
| path: english/validation.json |
| - split: test |
| path: english/test.json |
| - config_name: japanese |
| data_files: |
| - split: train |
| path: japanese/train.json |
| - split: validation |
| path: japanese/validation.json |
| - split: test |
| path: japanese/test.json |
| - config_name: korean |
| data_files: |
| - split: train |
| path: korean/train.json |
| - split: validation |
| path: korean/validation.json |
| - split: test |
| path: korean/test.json |
| - config_name: sinhala |
| data_files: |
| - split: train |
| path: sinhala/train.json |
| - split: validation |
| path: sinhala/validation.json |
| - split: test |
| path: sinhala/test.json |
| - config_name: tamil |
| data_files: |
| - split: train |
| path: tamil/train.json |
| - split: validation |
| path: tamil/validation.json |
| - split: test |
| path: tamil/test.json |
| --- |
| |
| # M2DS v1.0 — Multilingual Dataset for Multi-document Summarisation |
|
|
| M2DS is a multilingual multi-document summarisation dataset built from BBC news articles and |
| professionally written BBC summaries across five languages: English, Japanese, Korean, Sinhala, |
| and Tamil. |
|
|
| ## Quick start |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load a specific language |
| ds = load_dataset("KushanH/m2ds", "english") |
| |
| # Access splits |
| train = ds["train"] |
| val = ds["validation"] |
| test = ds["test"] |
| |
| # Inspect a single example |
| print(train[0]["document"]) # concatenated source articles |
| print(train[0]["summary"]) # reference summary |
| ``` |
|
|
| Available config names: `english`, `japanese`, `korean`, `sinhala`, `tamil`. |
|
|
| ## Dataset structure |
|
|
| Each language is released as split-based files compatible with Hugging Face `load_dataset()`. |
|
|
| ### Splits |
|
|
| | Split | Purpose | |
| |------------|--------------------------| |
| | `train` | Model training | |
| | `validation` | Hyperparameter tuning | |
| | `test` | Final evaluation | |
|
|
| ### Fields |
|
|
| Each row represents one **multi-document cluster** and contains two fields: |
|
|
| | Field | Type | Description | |
| |------------|--------|-------------------------------------------------------------------| |
| | `document` | string | Multiple related source articles concatenated into one text field | |
| | `summary` | string | Reference summary combining BBC summaries for the cluster | |
|
|
| ### Document separator |
|
|
| Within the `document` field, individual articles are separated by: |
|
|
| ``` |
| ||||| |
| ``` |
|
|
| Example: |
|
|
| ``` |
| Article one text here... ||||| Article two text here... ||||| Article three text here... |
| ``` |
|
|
| ## Split ratios |
|
|
| - English: **80 / 10 / 10** |
| - Japanese, Korean, Sinhala, Tamil: **90 / 5 / 5** |
|
|
| ## Statistics |
|
|
| | Language | Train | Validation | Test | Total | Paper | |
| |-----------|-------:|-----------:|------:|-------:|-------:| |
| | English | 13,496 | 1,688 | 1,687 | 16,871 | 17K | |
| | Japanese | 9,891 | 549 | 551 | 10,991 | 11K | |
| | Korean | 7,021 | 391 | 390 | 7,802 | 8K | |
| | Sinhala | 4,942 | 275 | 275 | 5,492 | 5.5K | |
| | Tamil | 8,916 | 495 | 496 | 9,907 | 10K | |
| | **Total** | **44,266** | **3,398** | **3,399** | **51,063** | **~51.5K** | |
|
|
| Paper-reported values are rounded per-language presentation values. |
|
|
| ## External resources |
|
|
| - OSF Archive: https://osf.io/7gjtm/ |
| - GitHub Repository: https://github.com/KushanMH/m2ds |
|
|
| ## License |
|
|
| The dataset structure, preprocessing pipeline, clustering methodology, metadata, and split definitions are released under the MIT License. |
|
|
| M2DS is constructed from publicly available BBC news articles and professionally written BBC summaries. |
|
|
| Original textual content remains subject to BBC copyright and applicable source terms. |
|
|
| This dataset is intended for research and educational purposes. |
|
|
| Users are responsible for ensuring compliance with original source rights when reusing the dataset. |
|
|
| ## Citation |
|
|
| If you use M2DS in your research, please cite: |
|
|
| ```bibtex |
| @inproceedings{hewapathirana2024m2ds, |
| title={M2DS: Multilingual Dataset for Multi-document Summarisation}, |
| author={Hewapathirana, Kushan and de Silva, Nisansa and Athuraliya, CD}, |
| booktitle={International Conference on Computational Collective Intelligence}, |
| pages={219--231}, |
| year={2024}, |
| organization={Springer} |
| } |
| ``` |
|
|
