web_nlg

• Description:

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.

• Additional Documentation: Explore on Papers With Code north_east

• Homepage: https://webnlg-challenge.loria.fr/challenge_2017/

• Source code: tfds.structured.web_nlg.WebNlg

• Versions:

  • 0.1.0 (default): No release notes.

• Download size: 19.76 MiB

• Dataset size: 13.78 MiB

• Auto-cached (documentation): Yes

• Splits:

• Feature structure:

FeaturesDict({
    'input_text': FeaturesDict({
        'context': string,
        'table': Sequence({
            'column_header': string,
            'content': string,
            'row_number': int16,
        }),
    }),
    'target_text': string,
})

• Feature documentation:

• Supervised keys (See as_supervised doc): ('input_text', 'target_text')

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@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""
}