Datasets:
totto

Languages: English
Multilinguality: monolingual
Size Categories: 100K<n<1M
Language Creators: found
Annotations Creators: expert-generated
Source Datasets: original
system
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Commit
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1 Parent(s): 93f534d

Update files from the datasets library (from 1.12.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.12.0

Files changed (3) hide show
  1. README.md +44 -23
  2. dataset_infos.json +1 -1
  3. totto.py +1 -1
README.md CHANGED
@@ -18,9 +18,10 @@ task_categories:
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  task_ids:
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  - table-to-text
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  paperswithcode_id: totto
 
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  ---
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- # Dataset Card Creation Guide
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
@@ -56,7 +57,8 @@ paperswithcode_id: totto
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  ### Dataset Summary
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- [More Information Needed]
 
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  ### Supported Tasks and Leaderboards
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@@ -70,25 +72,6 @@ paperswithcode_id: totto
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  ### Data Instances
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- ```
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- DatasetDict({
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- train: Dataset({
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- features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
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- num_rows: 120761
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- })
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- validation: Dataset({
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- features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
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- num_rows: 7700
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- })
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- test: Dataset({
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- features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
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- num_rows: 7700
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- })
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- })
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- ```
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-
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- ### Data Fields
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-
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  A sample training set is provided below
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  ```
@@ -385,9 +368,40 @@ A sample training set is provided below
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  Please note that in test set sentence annotations are not available and thus values inside `sentence_annotations` can be safely ignored.
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  ### Data Splits
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- [More Information Needed]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Dataset Creation
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  ### Curation Rationale
@@ -448,7 +462,14 @@ Please note that in test set sentence annotations are not available and thus val
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  ### Citation Information
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- [More Information Needed]
 
 
 
 
 
 
 
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  ### Contributions
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  task_ids:
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  - table-to-text
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  paperswithcode_id: totto
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+ pretty_name: ToTTo
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  ---
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+ # Dataset Card for ToTTo
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
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  ### Dataset Summary
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+ ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled
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+ generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.
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  ### Supported Tasks and Leaderboards
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  ### Data Instances
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  A sample training set is provided below
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  ```
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  Please note that in test set sentence annotations are not available and thus values inside `sentence_annotations` can be safely ignored.
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+ ### Data Fields
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+
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+ - `table_webpage_url` (`str`): Table webpage URL.
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+ - `table_page_title` (`str`): Table metadata with context about the table.
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+ - `table_section_title` (`str`): Table metadata with context about the table.
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+ - `table_section_text` (`str`): Table metadata with context about the table.
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+ - `table` (`List[List[Dict]]`): The outer lists represents rows and the inner lists columns. Each Dict has the fields:
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+ - `column_span` (`int`)
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+ - `is_header` (`bool`)
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+ - `row_span` (`int`)
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+ - `value` (`str`)
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+ - `highlighted_cells` (`List[[row_index, column_index]]`): Where each `[row_index, column_index]` pair indicates that `table[row_index][column_index]` is highlighted.
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+ - `example_id` (`int`): A unique id for this example.
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+ - `sentence_annotations`: Consists of the `original_sentence` and the sequence of revised sentences performed in order to produce the `final_sentence`.
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+
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  ### Data Splits
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+ ```
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+ DatasetDict({
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+ train: Dataset({
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+ features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
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+ num_rows: 120761
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+ })
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+ validation: Dataset({
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+ features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
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+ num_rows: 7700
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+ })
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+ test: Dataset({
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+ features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
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+ num_rows: 7700
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+ })
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+ })
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+ ```
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+
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  ## Dataset Creation
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  ### Curation Rationale
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  ### Citation Information
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+ ```
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+ @inproceedings{parikh2020totto,
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+ title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},
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+ author={Parikh, Ankur P and Wang, Xuezhi and Gehrmann, Sebastian and Faruqui, Manaal and Dhingra, Bhuwan and Yang, Diyi and Das, Dipanjan},
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+ booktitle={Proceedings of EMNLP},
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+ year={2020}
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+ }
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+ ```
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  ### Contributions
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dataset_infos.json CHANGED
@@ -1 +1 @@
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- {"default": {"description": "ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.\n", "citation": "@inproceedings{parikh2020totto,\n title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},\n author={Parikh, Ankur P and Wang, Xuezhi and Gehrmann, Sebastian and Faruqui, Manaal and Dhingra, Bhuwan and Yang, Diyi and Das, Dipanjan},\n booktitle={Proceedings of EMNLP},\n year={2020}\n }\n", "homepage": "", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "table_page_title": {"dtype": "string", "id": null, "_type": "Value"}, "table_webpage_url": {"dtype": "string", "id": null, "_type": "Value"}, "table_section_title": {"dtype": "string", "id": null, "_type": "Value"}, "table_section_text": {"dtype": "string", "id": null, "_type": "Value"}, "table": [[{"column_span": {"dtype": "int32", "id": null, "_type": "Value"}, "is_header": {"dtype": "bool", "id": null, "_type": "Value"}, "row_span": {"dtype": "int32", "id": null, "_type": "Value"}, "value": {"dtype": "string", "id": null, "_type": "Value"}}]], "highlighted_cells": {"feature": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "example_id": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_annotations": {"feature": {"original_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_after_deletion": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_after_ambiguity": {"dtype": "string", "id": null, "_type": "Value"}, "final_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "overlap_subset": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "totto", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 652754806, "num_examples": 120761, "dataset_name": "totto"}, "validation": {"name": "validation", "num_bytes": 47277039, "num_examples": 7700, "dataset_name": "totto"}, "test": {"name": "test", "num_bytes": 40883586, "num_examples": 7700, "dataset_name": "totto"}}, "download_checksums": {"https://storage.googleapis.com/totto/totto_data.zip": {"num_bytes": 187724372, "checksum": "0aab72597057394514fd9659745fd2b318d1a64bf0b2ca1b2c339abe0692fdf2"}}, "download_size": 187724372, "post_processing_size": null, "dataset_size": 740915431, "size_in_bytes": 928639803}}
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+ {"default": {"description": "ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.\n", "citation": "@inproceedings{parikh2020totto,\n title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},\n author={Parikh, Ankur P and Wang, Xuezhi and Gehrmann, Sebastian and Faruqui, Manaal and Dhingra, Bhuwan and Yang, Diyi and Das, Dipanjan},\n booktitle={Proceedings of EMNLP},\n year={2020}\n }\n", "homepage": "", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "table_page_title": {"dtype": "string", "id": null, "_type": "Value"}, "table_webpage_url": {"dtype": "string", "id": null, "_type": "Value"}, "table_section_title": {"dtype": "string", "id": null, "_type": "Value"}, "table_section_text": {"dtype": "string", "id": null, "_type": "Value"}, "table": [[{"column_span": {"dtype": "int32", "id": null, "_type": "Value"}, "is_header": {"dtype": "bool", "id": null, "_type": "Value"}, "row_span": {"dtype": "int32", "id": null, "_type": "Value"}, "value": {"dtype": "string", "id": null, "_type": "Value"}}]], "highlighted_cells": {"feature": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "example_id": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_annotations": {"feature": {"original_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_after_deletion": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_after_ambiguity": {"dtype": "string", "id": null, "_type": "Value"}, "final_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "overlap_subset": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "totto", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 652754806, "num_examples": 120761, "dataset_name": "totto"}, "validation": {"name": "validation", "num_bytes": 47277039, "num_examples": 7700, "dataset_name": "totto"}, "test": {"name": "test", "num_bytes": 40883586, "num_examples": 7700, "dataset_name": "totto"}}, "download_checksums": {"https://storage.googleapis.com/totto-public/totto_data.zip": {"num_bytes": 187724372, "checksum": "0aab72597057394514fd9659745fd2b318d1a64bf0b2ca1b2c339abe0692fdf2"}}, "download_size": 187724372, "post_processing_size": null, "dataset_size": 740915431, "size_in_bytes": 928639803}}
totto.py CHANGED
@@ -24,7 +24,7 @@ _DESCRIPTION = """\
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  ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.
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  """
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  _HOMEPAGE_URL = ""
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- _URL = "https://storage.googleapis.com/totto/totto_data.zip"
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  _CITATION = """\
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  @inproceedings{parikh2020totto,
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  title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},
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  ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.
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  """
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  _HOMEPAGE_URL = ""
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+ _URL = "https://storage.googleapis.com/totto-public/totto_data.zip"
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  _CITATION = """\
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  @inproceedings{parikh2020totto,
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  title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},