The WebNLG Challenge: Generating Text from RDF Data

Claire Gardent, Anastasia Shimorina, Shashi Narayan, Laura Perez-Beltrachini

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The WebNLG challenge consists in mapping sets of RDF triples to text. It provides a common benchmark on which to train, evaluate and compare “microplanners”, i.e. generation systems that verbalise a given content by making a range of complex interacting choices including referring expression generation, aggregation, lexicalisation, surface realisation and sentence segmentation. In this paper, we introduce the microplanning task, describe data preparation, introduce our evaluation methodology, analyse participant results and provide a brief description of the participating systems.
Original languageEnglish
Title of host publicationProceedings of the 10th International Natural Language Generation conference (INLG)
PublisherACL Anthology
Number of pages10
Publication statusPublished - 7 Sep 2017
Event10th International Conference on Natural Language Generation - Santiago de Compostela, Spain
Duration: 4 Sep 20177 Sep 2017


Conference10th International Conference on Natural Language Generation
Abbreviated titleINLG 2017
CitySantiago de Compostela
Internet address


Dive into the research topics of 'The WebNLG Challenge: Generating Text from RDF Data'. Together they form a unique fingerprint.

Cite this