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--- |
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license: cc |
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language: |
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- ach |
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- ada |
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- aeb |
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- afr |
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pretty_name: GlotStoryBook Corpus |
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tags: |
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- storybook |
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- book |
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- story |
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- language-identification |
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- nalibali |
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- machine-translation |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: GlotStoryBook.csv |
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- config_name: nalibali |
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data_files: |
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- split: train |
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path: nalibali.csv |
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task_categories: |
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- translation |
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- text-generation |
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- text2text-generation |
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- summarization |
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--- |
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## Dataset Description |
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Story Books for 180 ISO-639-3 codes. |
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The `Parallel ID` or `parallel_id` can be used to find the parallel documents in different languages and build a parallel dataset. |
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This dataset consists of 2 subsets: |
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- **default**, which consists of 4 publishers: |
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1. asp: [African Storybook](https://africanstorybook.org) |
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2. pb: [Pratham Books](https://prathambooks.org/) |
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3. lcb: [Little Cree Books](http://littlecreebooks.com/) |
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4. lida: [LIDA Stories](https://lidastories.net/) |
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- **nalibali**, which comes from [Nal'ibali](https://nalibali.org/story-resources/multilingual-stories) stories. |
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## Usage (HF Loader) |
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- default: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset('cis-lmu/GlotStoryBook', 'default', split='train') |
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print(dataset[0]) # First row of default data |
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``` |
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- nalibali: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset('cis-lmu/GlotStoryBook', 'nalibali', split='train') |
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print(dataset[0]) # First row of nalibali data |
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``` |
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## Download |
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If you are not a fan of the HF dataloader, download it directly: |
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- default: |
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```python |
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! wget https://huggingface.co/datasets/cis-lmu/GlotStoryBook/resolve/main/GlotStoryBook.csv |
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``` |
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- nalibali: |
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```python |
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! wget https://huggingface.co/datasets/cis-lmu/GlotStoryBook/resolve/main/nalibali.csv |
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``` |
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# Tools |
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To compute the script of each text we used Glotscript ([code](https://github.com/cisnlp/GlotScript) and [paper](https://arxiv.org/abs/2309.13320)). |
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## License and Copyright |
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- default: |
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We do not own any of the text from which these data has been extracted. |
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All the files are collected from the repository located at https://github.com/global-asp/. |
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The source repository for each text and file is stored in the dataset. |
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Each file in the dataset is associated with one license from the CC family. |
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The licenses include 'CC BY', 'CC BY-NC', 'CC BY-NC-SA', 'CC-BY', 'CC-BY-NC', and 'Public Domain'. |
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We also license the code, actual packaging and the metadata of these data under the cc0-1.0. |
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- nalibali: |
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We do not own any of the text from which these data has been extracted. |
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All the files are collected from [https://nalibali.org](https://nalibali.org/story-resources/multilingual-stories) under the [nalibali term of use](https://nalibali.org/terms-use): |
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> Material on this website may be freely downloaded, shared and reprinted. In fact, we welcome the circulation and sharing of Nal’ibali resources, provided it adheres to the following guidelines: It is credited to the Nal’ibali initiative, and retains the Nal’ibali logo and web address wherever possible; it is for personal, educational and developmental purposes only; it may not be sold, used or distributed commercially or for a fee. |
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We also license the code, actual packaging and the metadata of these data under the cc0-1.0. |
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## Github |
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We additionally provide a GitHub version that openly shares the source code for processing this dataset: |
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https://github.com/cisnlp/GlotStoryBook |
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## Citation |
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If you use any part of this code and data in your research, please cite it (along with https://github.com/global-asp/ and https://nalibali.org) using the following BibTeX entry. |
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This work is part of the [GlotLID](https://github.com/cisnlp/GlotLID) project and [paper](https://arxiv.org/abs/2310.16248). |
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|
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``` |
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@inproceedings{ |
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kargaran2023glotlid, |
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title={{GlotLID}: Language Identification for Low-Resource Languages}, |
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author={Kargaran, Amir Hossein and Imani, Ayyoob and Yvon, Fran{\c{c}}ois and Sch{\"u}tze, Hinrich}, |
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booktitle={The 2023 Conference on Empirical Methods in Natural Language Processing}, |
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year={2023}, |
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url={https://openreview.net/forum?id=dl4e3EBz5j} |
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} |
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|
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``` |