web_nlg
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The data contains sets of 1 to 7 triples of the form subject-predicate-object
extracted from (DBpedia)[https://wiki.dbpedia.org/] and natural language text
that's a verbalisation of these triples. The test data spans 15 different
domains where only 10 appear in the training data. The dataset follows a
standarized table format.
| Split |
Examples |
'test_all' |
4,928 |
'test_unseen' |
2,433 |
'train' |
18,102 |
'validation' |
2,268 |
FeaturesDict({
'input_text': FeaturesDict({
'context': string,
'table': Sequence({
'column_header': string,
'content': string,
'row_number': int16,
}),
}),
'target_text': string,
})
| Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
| input_text |
FeaturesDict |
|
|
|
| input_text/context |
Tensor |
|
string |
|
| input_text/table |
Sequence |
|
|
|
| input_text/table/column_header |
Tensor |
|
string |
|
| input_text/table/content |
Tensor |
|
string |
|
| input_text/table/row_number |
Tensor |
|
int16 |
|
| target_text |
Tensor |
|
string |
|
@inproceedings{gardent2017creating,
title = ""Creating Training Corpora for {NLG} Micro-Planners"",
author = ""Gardent, Claire and
Shimorina, Anastasia and
Narayan, Shashi and
Perez-Beltrachini, Laura"",
booktitle = ""Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)"",
month = jul,
year = ""2017"",
address = ""Vancouver, Canada"",
publisher = ""Association for Computational Linguistics"",
doi = ""10.18653/v1/P17-1017"",
pages = ""179--188"",
url = ""https://www.aclweb.org/anthology/P17-1017.pdf""
}
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Last updated 2022-12-06 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2022-12-06 UTC."],[],[],null,["# web_nlg\n\n\u003cbr /\u003e\n\n- **Description**:\n\nThe data contains sets of 1 to 7 triples of the form subject-predicate-object\nextracted from (DBpedia)\\[\u003chttps://wiki.dbpedia.org/\u003e\\] and natural language text\nthat's a verbalisation of these triples. The test data spans 15 different\ndomains where only 10 appear in the training data. The dataset follows a\nstandarized table format.\n\n- **Additional Documentation** :\n [Explore on Papers With Code\n north_east](https://paperswithcode.com/dataset/webnlg)\n\n- **Homepage** :\n \u003chttps://webnlg-challenge.loria.fr/challenge_2017/\u003e\n\n- **Source code** :\n [`tfds.structured.web_nlg.WebNlg`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/structured/web_nlg/web_nlg.py)\n\n- **Versions**:\n\n - **`0.1.0`** (default): No release notes.\n- **Download size** : `19.76 MiB`\n\n- **Dataset size** : `13.78 MiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n Yes\n\n- **Splits**:\n\n| Split | Examples |\n|-----------------|----------|\n| `'test_all'` | 4,928 |\n| `'test_unseen'` | 2,433 |\n| `'train'` | 18,102 |\n| `'validation'` | 2,268 |\n\n- **Feature structure**:\n\n FeaturesDict({\n 'input_text': FeaturesDict({\n 'context': string,\n 'table': Sequence({\n 'column_header': string,\n 'content': string,\n 'row_number': int16,\n }),\n }),\n 'target_text': string,\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|--------------------------------|--------------|-------|--------|-------------|\n| | FeaturesDict | | | |\n| input_text | FeaturesDict | | | |\n| input_text/context | Tensor | | string | |\n| input_text/table | Sequence | | | |\n| input_text/table/column_header | Tensor | | string | |\n| input_text/table/content | Tensor | | string | |\n| input_text/table/row_number | Tensor | | int16 | |\n| target_text | Tensor | | string | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `('input_text', 'target_text')`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Examples**\n ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\n- **Citation**:\n\n @inproceedings{gardent2017creating,\n title = \"\"Creating Training Corpora for {NLG} Micro-Planners\"\",\n author = \"\"Gardent, Claire and\n Shimorina, Anastasia and\n Narayan, Shashi and\n Perez-Beltrachini, Laura\"\",\n booktitle = \"\"Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)\"\",\n month = jul,\n year = \"\"2017\"\",\n address = \"\"Vancouver, Canada\"\",\n publisher = \"\"Association for Computational Linguistics\"\",\n doi = \"\"10.18653/v1/P17-1017\"\",\n pages = \"\"179--188\"\",\n url = \"\"https://www.aclweb.org/anthology/P17-1017.pdf\"\"\n }"]]
