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--- |
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annotations_creators: |
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- machine-generated |
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language: |
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- ar |
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- es |
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- fr |
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- de |
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- hi |
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- it |
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- ja |
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- nl |
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- pt |
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language_creators: |
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- found |
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license_details: https://huggingface.co/datasets/AmazonScience/xtr-wiki_qa/blob/main/LICENSE.md |
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multilinguality: |
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- multilingual |
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- translation |
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pretty_name: xtr-wiki_qa |
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size_categories: |
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- 100K<n<1M |
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source_datasets: |
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- extended|wiki_qa |
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tags: |
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- as2 |
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- answer sentence selection |
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- text retrieval |
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- question answering |
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task_categories: |
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- question-answering |
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- text-retrieval |
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task_ids: |
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- open-domain-qa |
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license: cdla-permissive-2.0 |
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--- |
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# Xtr-WikiQA |
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## Table of Contents |
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- [Dataset Card Creation Guide](#dataset-card-creation-guide) |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Source Data](#source-data) |
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- [Additional Information](#additional-information) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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- **Homepage:** [Amazon Science](https://www.amazon.science/publications/cross-lingual-knowledge-distillation-for-answer-sentence-selection-in-low-resource-languages) |
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- **Paper:** [Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages](https://aclanthology.org/2023.findings-acl.885/) |
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- **Point of Contact:** [Yoshitomo Matsubara]([email protected]) |
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### Dataset Summary |
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***Xtr-WikiQA*** is an Answer Sentence Selection (AS2) dataset in 9 non-English languages, proposed in our paper accepted at ACL 2023 (Findings): [**Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages**](https://aclanthology.org/2023.findings-acl.885/). |
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This dataset is based on an English AS2 dataset, WikiQA ([Original](https://msropendata.com/datasets/21032bb1-88bd-4656-9570-3172ae1757f0), [Hugging Face](https://huggingface.co/datasets/wiki_qa)). |
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For translations, we used [Amazon Translate](https://aws.amazon.com/translate/). |
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### Languages |
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- Arabic (ar) |
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- Spanish (es) |
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- French (fr) |
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- German (de) |
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- Hindi (hi) |
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- Italian (it) |
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- Japanese (ja) |
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- Dutch (nl) |
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- Portuguese (pt) |
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File location: [`tsv/`](https://huggingface.co/datasets/AmazonScience/xtr-wiki_qa/tree/main/tsv) |
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## Dataset Structure |
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### Data Instances |
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This is an example instance from the Arabic training split of Xtr-WikiQA dataset. |
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``` |
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{ |
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"QuestionID": "Q1", |
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"Question": "ููู ุชุชุดูู ุงููููู ุงูุฌููุฏูุฉุ", |
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"DocumentID": "D1", |
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"DocumentTitle": "ููู ุฌููุฏู", |
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"SentenceID": "D1-0", |
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"Sentence": "ููู ุฌููุฏู ู
ุบู
ูุฑ ุฌุฒุฆููุง ุนูู ููุฑ ุจูุฑูุชู ู
ูุฑููู ุงูุฌููุฏู.", |
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"Label": 0 |
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} |
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``` |
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All the translated instances in tsv files are listed in the same order of the original (native) instances in the WikiQA dataset. |
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For example, the 2nd instance in [`tsv/ar-train.tsv`](https://huggingface.co/datasets/AmazonScience/xtr-wiki_qa/blob/main/tsv/ar-train.tsv) (Arabic-translated from English) |
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corresponds to the 2nd instance in [`WikiQA-train.tsv`](https://msropendata.com/datasets/21032bb1-88bd-4656-9570-3172ae1757f0) (English). |
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### Data Fields |
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Each instance (a QA pair) consists of the following fields: |
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- `QuestionID`: Question ID (str) |
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- `Question`: Question to be answered (str) |
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- `DocumentID`: Document ID (str) |
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- `DocumentTitle`: Document title (str) |
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- `SentenceID`: Answer sentence in the document (str) |
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- `Sentence`: Answer sentence in the document (str) |
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- `Label`: Label that indicates the answer sentence correctly answers the question (int, 1: correct, 0: incorrect) |
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### Data Splits |
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| | | **#Questions** | | | | **#Sentences** | | |
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|-------------------|------------:|---------------:|---------:|---|----------:|---------------:|---------:| |
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| | **train** | **dev** | **test** | | **train** | **dev** | **test** | |
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| **Each language** | 873 | 126 | 243 | | 8,671 | 1,130 | 2,351 | |
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See [our paper](#citation-information) for more details about the statistics of the datasets. |
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## Dataset Creation |
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### Source Data |
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The source of Xtr-WikiQA dataset is [WikiQA](https://msropendata.com/datasets/21032bb1-88bd-4656-9570-3172ae1757f0). |
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## Additional Information |
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### Licensing Information |
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[CDLA-Permissive-2.0](LICENSE.md) |
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### Citation Information |
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```bibtex |
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@inproceedings{gupta2023cross-lingual, |
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title={{Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages}}, |
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author={Gupta, Shivanshu and Matsubara, Yoshitomo and Chadha, Ankit and Moschitti, Alessandro}, |
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booktitle={Findings of the Association for Computational Linguistics: ACL 2023}, |
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pages={14078--14092}, |
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year={2023} |
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} |
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``` |
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### Contributions |
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- [Shivanshu Gupta](https://huggingface.co/shivanshu) |
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- [Yoshitomo Matsubara](https://huggingface.co/yoshitomo-matsubara) |
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- Ankit Chadha |
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- Alessandro Moschitti |
