Datasets:
Tasks:
Question Answering
Sub-tasks:
extractive-qa
Multilinguality:
multilingual
Size Categories:
unknown
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
extended|wikipedia
ArXiv:
Tags:
License:
| pretty_name: TyDi QA | |
| annotations_creators: | |
| - crowdsourced | |
| language_creators: | |
| - crowdsourced | |
| language: | |
| - en | |
| - ar | |
| - bn | |
| - fi | |
| - id | |
| - ja | |
| - sw | |
| - ko | |
| - ru | |
| - te | |
| - th | |
| license: | |
| - apache-2.0 | |
| multilinguality: | |
| - multilingual | |
| size_categories: | |
| - unknown | |
| source_datasets: | |
| - extended|wikipedia | |
| task_categories: | |
| - question-answering | |
| task_ids: | |
| - extractive-qa | |
| paperswithcode_id: tydi-qa | |
| # Dataset Card for "tydiqa" | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [https://github.com/google-research-datasets/tydiqa](https://github.com/google-research-datasets/tydiqa) | |
| - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| - **Size of downloaded dataset files:** 3726.74 MB | |
| - **Size of the generated dataset:** 5812.92 MB | |
| - **Total amount of disk used:** 9539.67 MB | |
| ### Dataset Summary | |
| TyDi QA is a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs. | |
| The languages of TyDi QA are diverse with regard to their typology -- the set of linguistic features that each language | |
| expresses -- such that we expect models performing well on this set to generalize across a large number of the languages | |
| in the world. It contains language phenomena that would not be found in English-only corpora. To provide a realistic | |
| information-seeking task and avoid priming effects, questions are written by people who want to know the answer, but | |
| don’t know the answer yet, (unlike SQuAD and its descendents) and the data is collected directly in each language without | |
| the use of translation (unlike MLQA and XQuAD). | |
| We also include "translate-train" and "translate-test" splits for each non-English languages from XTREME (Hu et al., 2020). These splits are the automatic translations from English to each target language used in the XTREME paper [https://arxiv.org/abs/2003.11080]. The "translate-train" split purposefully ignores the non-English TyDiQA-GoldP training data to simulate the transfer learning scenario where original-language data is not available and system builders must rely on labeled English data plus existing machine translation systems. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Languages | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Dataset Structure | |
| ### Data Instances | |
| #### primary_task | |
| - **Size of downloaded dataset files:** 1863.37 MB | |
| - **Size of the generated dataset:** 5757.59 MB | |
| - **Total amount of disk used:** 7620.96 MB | |
| An example of 'validation' looks as follows. | |
| ``` | |
| This example was too long and was cropped: | |
| { | |
| "annotations": { | |
| "minimal_answers_end_byte": [-1, -1, -1], | |
| "minimal_answers_start_byte": [-1, -1, -1], | |
| "passage_answer_candidate_index": [-1, -1, -1], | |
| "yes_no_answer": ["NONE", "NONE", "NONE"] | |
| }, | |
| "document_plaintext": "\"\\nรองศาสตราจารย์[1] หม่อมราชวงศ์สุขุมพันธุ์ บริพัตร (22 กันยายน 2495 -) ผู้ว่าราชการกรุงเทพมหานครคนที่ 15 อดีตรองหัวหน้าพรรคปร...", | |
| "document_title": "หม่อมราชวงศ์สุขุมพันธุ์ บริพัตร", | |
| "document_url": "\"https://th.wikipedia.org/wiki/%E0%B8%AB%E0%B8%A1%E0%B9%88%E0%B8%AD%E0%B8%A1%E0%B8%A3%E0%B8%B2%E0%B8%8A%E0%B8%A7%E0%B8%87%E0%B8%...", | |
| "language": "thai", | |
| "passage_answer_candidates": "{\"plaintext_end_byte\": [494, 1779, 2931, 3904, 4506, 5588, 6383, 7122, 8224, 9375, 10473, 12563, 15134, 17765, 19863, 21902, 229...", | |
| "question_text": "\"หม่อมราชวงศ์สุขุมพันธุ์ บริพัตร เรียนจบจากที่ไหน ?\"..." | |
| } | |
| ``` | |
| #### secondary_task | |
| - **Size of downloaded dataset files:** 1863.37 MB | |
| - **Size of the generated dataset:** 55.34 MB | |
| - **Total amount of disk used:** 1918.71 MB | |
| An example of 'validation' looks as follows. | |
| ``` | |
| This example was too long and was cropped: | |
| { | |
| "answers": { | |
| "answer_start": [394], | |
| "text": ["بطولتين"] | |
| }, | |
| "context": "\"أقيمت البطولة 21 مرة، شارك في النهائيات 78 دولة، وعدد الفرق التي فازت بالبطولة حتى الآن 8 فرق، ويعد المنتخب البرازيلي الأكثر تت...", | |
| "id": "arabic-2387335860751143628-1", | |
| "question": "\"كم عدد مرات فوز الأوروغواي ببطولة كاس العالم لكرو القدم؟\"...", | |
| "title": "قائمة نهائيات كأس العالم" | |
| } | |
| ``` | |
| ### Data Fields | |
| The data fields are the same among all splits. | |
| #### primary_task | |
| - `passage_answer_candidates`: a dictionary feature containing: | |
| - `plaintext_start_byte`: a `int32` feature. | |
| - `plaintext_end_byte`: a `int32` feature. | |
| - `question_text`: a `string` feature. | |
| - `document_title`: a `string` feature. | |
| - `language`: a `string` feature. | |
| - `annotations`: a dictionary feature containing: | |
| - `passage_answer_candidate_index`: a `int32` feature. | |
| - `minimal_answers_start_byte`: a `int32` feature. | |
| - `minimal_answers_end_byte`: a `int32` feature. | |
| - `yes_no_answer`: a `string` feature. | |
| - `document_plaintext`: a `string` feature. | |
| - `document_url`: a `string` feature. | |
| #### secondary_task | |
| - `id`: a `string` feature. | |
| - `title`: a `string` feature. | |
| - `context`: a `string` feature. | |
| - `question`: a `string` feature. | |
| - `answers`: a dictionary feature containing: | |
| - `text`: a `string` feature. | |
| - `answer_start`: a `int32` feature. | |
| ### Data Splits | |
| | name | train | validation | | |
| | -------------- | -----: | ---------: | | |
| | primary_task | 166916 | 18670 | | |
| | secondary_task | 49881 | 5077 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the source language producers? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the annotators? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Personal and Sensitive Information | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Discussion of Biases | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Other Known Limitations | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Licensing Information | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Citation Information | |
| ``` | |
| @article{tydiqa, | |
| title = {TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages}, | |
| author = {Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki} | |
| year = {2020}, | |
| journal = {Transactions of the Association for Computational Linguistics} | |
| } | |
| ``` | |
| ``` | |
| @inproceedings{ruder-etal-2021-xtreme, | |
| title = "{XTREME}-{R}: Towards More Challenging and Nuanced Multilingual Evaluation", | |
| author = "Ruder, Sebastian and | |
| Constant, Noah and | |
| Botha, Jan and | |
| Siddhant, Aditya and | |
| Firat, Orhan and | |
| Fu, Jinlan and | |
| Liu, Pengfei and | |
| Hu, Junjie and | |
| Garrette, Dan and | |
| Neubig, Graham and | |
| Johnson, Melvin", | |
| booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing", | |
| month = nov, | |
| year = "2021", | |
| address = "Online and Punta Cana, Dominican Republic", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/2021.emnlp-main.802", | |
| doi = "10.18653/v1/2021.emnlp-main.802", | |
| pages = "10215--10245", | |
| } | |
| } | |
| ``` | |