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- ---
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- annotations_creators:
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- - expert-generated
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- - crowdsourced
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- language:
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- - en
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- language_creators:
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- - found
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- - crowdsourced
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- - expert-generated
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- license:
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- - c-uda
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- multilinguality:
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- - monolingual
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- paperswithcode_id: totto
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- pretty_name: HiTab
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- size_categories:
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- - 10K<n<100K
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- source_datasets:
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- - original
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- - extended|totto
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- tags: []
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- task_categories:
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- - table-to-text
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- - question-answering
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- task_ids: []
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- dataset_info:
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- features:
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- - name: id
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- dtype: string
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- - name: table_id
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- dtype: string
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- - name: table_source
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- dtype: string
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- - name: sentence_id
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- dtype: string
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- - name: sub_sentence_id
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- dtype: string
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- - name: sub_sentence
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- dtype: string
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- - name: question
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- dtype: string
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- - name: answer
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- dtype: large_string
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- - name: aggregation
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- dtype: large_string
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- - name: linked_cells
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- dtype: large_string
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- - name: answer_formulas
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- dtype: large_string
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- - name: reference_cells_map
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- dtype: large_string
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- - name: table_content
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- dtype: large_string
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- splits:
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- - name: train
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- num_bytes: 36419103
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- num_examples: 7417
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- - name: validation
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- num_bytes: 8312699
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- num_examples: 1671
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- - name: test
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- num_bytes: 7710891
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- num_examples: 1584
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- download_size: 6462957
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- dataset_size: 52442693
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- ---
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-
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- # Dataset Card for HiTab
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-
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- ## Dataset Description
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- - **Homepage:** https://www.microsoft.com/en-us/research/publication/hitab-a-hierarchical-table-dataset-for-question-answering-and-natural-language-generation/
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- - **Repository:** https://github.com/microsoft/HiTab/blob/main/LICENSE
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- - **Paper:** https://aclanthology.org/2022.acl-long.78/
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-
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- ### Dataset Summary
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- HiTab is a dataset for question answering and data-to-text over hierarchical tables . It contains 10,672 samples and 3,597 tables from statistical reports (StatCan, NSF) and Wikipedia (ToTTo). 98.1% of the tables in HiTab are with hierarchies.
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-
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- ### Supported Tasks and Leaderboards
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- Table-to-Text Generation, Question Answering
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-
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- ### Languages
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- English
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-
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- ### Data Instances
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- 3,597 tables, 10,686 sentences
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-
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- ### Data Splits
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- train, test, validation
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-
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- ## Dataset Creation
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- During the dataset annotation process, annotators first manually collect tables and descriptive sentences highly-related to tables on statistical websites written by professional analysts. Then these descriptions are revised to questions to preserve the original meanings and analyses.
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-
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- ### Licensing Information
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-
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- This dataset follows the Computational Use of Data Agreement v1.0.
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-
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- ### Citation Information
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-
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- ```
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- @article{cheng2021hitab,
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- title={HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation},
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- author={Cheng, Zhoujun and Dong, Haoyu and Wang, Zhiruo and Jia, Ran and Guo, Jiaqi and Gao, Yan and Han, Shi and Lou, Jian-Guang and Zhang, Dongmei},
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- journal={arXiv preprint arXiv:2108.06712},
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- year={2021}
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- }