Datasets:
Tasks:
Question Answering
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
License:
| annotations_creators: | |
| - crowdsourced | |
| language_creators: | |
| - crowdsourced | |
| language: | |
| - en | |
| license: | |
| - cc-by-4.0 | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - question-answering | |
| task_ids: [] | |
| paperswithcode_id: hybridqa | |
| pretty_name: HybridQA | |
| tags: | |
| - multihop-tabular-text-qa | |
| dataset_info: | |
| config_name: hybrid_qa | |
| features: | |
| - name: question_id | |
| dtype: string | |
| - name: question | |
| dtype: string | |
| - name: table_id | |
| dtype: string | |
| - name: answer_text | |
| dtype: string | |
| - name: question_postag | |
| dtype: string | |
| - name: table | |
| struct: | |
| - name: url | |
| dtype: string | |
| - name: title | |
| dtype: string | |
| - name: header | |
| sequence: string | |
| - name: data | |
| list: | |
| - name: value | |
| dtype: string | |
| - name: urls | |
| list: | |
| - name: url | |
| dtype: string | |
| - name: summary | |
| dtype: string | |
| - name: section_title | |
| dtype: string | |
| - name: section_text | |
| dtype: string | |
| - name: uid | |
| dtype: string | |
| - name: intro | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 2745712265 | |
| num_examples: 62682 | |
| - name: validation | |
| num_bytes: 153511944 | |
| num_examples: 3466 | |
| - name: test | |
| num_bytes: 148795847 | |
| num_examples: 3463 | |
| download_size: 217436855 | |
| dataset_size: 3048020056 | |
| # Dataset Card for HybridQA | |
| ## 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://hybridqa.github.io/index.html | |
| - **Repository:** [GitHub](https://github.com/wenhuchen/HybridQA) | |
| - **Paper:** [HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data](https://arxiv.org/abs/1909.05358) | |
| - **Leaderboard:** [HybridQA Competition](https://competitions.codalab.org/competitions/24420) | |
| - **Point of Contact:** [Wenhu Chen](wenhuchen@cs.ucsb.edu) | |
| ### Dataset Summary | |
| Existing question answering datasets focus on dealing with homogeneous information, based either only on text or | |
| KB/Table information alone. However, as human knowledge is distributed over heterogeneous forms, | |
| using homogeneous information alone might lead to severe coverage problems. | |
| To fill in the gap, we present HybridQA, a new large-scale question-answering dataset that | |
| requires reasoning on heterogeneous information. Each question is aligned with a Wikipedia table | |
| and multiple free-form corpora linked with the entities in the table. The questions are designed | |
| to aggregate both tabular information and text information, i.e., | |
| lack of either form would render the question unanswerable. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed] | |
| ### Languages | |
| The dataset is in English language. | |
| ## Dataset Structure | |
| ### Data Instances | |
| A typical example looks like this | |
| ``` | |
| { | |
| "question_id": "00009b9649d0dd0a", | |
| "question": "Who were the builders of the mosque in Herat with fire temples ?", | |
| "table_id": "List_of_mosques_in_Afghanistan_0", | |
| "answer_text": "Ghurids", | |
| "question_postag": "WP VBD DT NNS IN DT NN IN NNP IN NN NNS .", | |
| "table": { | |
| "url": "https://en.wikipedia.org/wiki/List_of_mosques_in_Afghanistan", | |
| "title": "List of mosques in Afghanistan", | |
| "header": [ | |
| "Name", | |
| "Province", | |
| "City", | |
| "Year", | |
| "Remarks" | |
| ], | |
| "data": [ | |
| { | |
| "value": "Kabul", | |
| "urls": [ | |
| { | |
| "summary": "Kabul ( Persian : کابل , romanized : Kābol , Pashto : کابل , romanized : Kābəl ) is the capital and largest city of Afghanistan...", | |
| "url": "/wiki/Kabul" | |
| } | |
| ] | |
| } | |
| ] | |
| }, | |
| "section_title": "", | |
| "section_text": "", | |
| "uid": "List_of_mosques_in_Afghanistan_0", | |
| "intro": "The following is an incomplete list of large mosques in Afghanistan:" | |
| } | |
| ``` | |
| ### Data Fields | |
| - `question_id` (str) | |
| - `question` (str) | |
| - `table_id` (str) | |
| - `answer_text` (str) | |
| - `question_postag` (str) | |
| - `table` (dict): | |
| - `url` (str) | |
| - `title` (str) | |
| - `header` (list of str) | |
| - `data` (list of dict): | |
| - `value` (str) | |
| - `urls` (list of dict): | |
| - `url` (str) | |
| - `summary` (str) | |
| - `section_title` (str) | |
| - `section_text` (str) | |
| - `uid` (str) | |
| - `intro` (str) | |
| ### Data Splits | |
| The dataset is split into `train`, `dev` and `test` splits. | |
| | | train | validation | test | | |
| | --------------- |------:|-----------:|-----:| | |
| | N. Instances | 62682 | 3466 | 3463 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| [More Information Needed] | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| [More Information Needed] | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| [More Information Needed] | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed] | |
| ### Licensing Information | |
| The dataset is under a [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/). | |
| ### Citation Information | |
| [More Information Needed] | |
| ``` | |
| @article{chen2020hybridqa, | |
| title={HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data}, | |
| author={Chen, Wenhu and Zha, Hanwen and Chen, Zhiyu and Xiong, Wenhan and Wang, Hong and Wang, William}, | |
| journal={Findings of EMNLP 2020}, | |
| year={2020} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset. | |