ML Anthology

Point at the Triple: Generation of Text Summaries from Knowledge Base Triples

Pavlos Vougiouklis, Eddy Maddalena, Jonathon S. Hare, Elena Simperl
JAIR 2020 pp. 1-31
doi:10.1613/JAIR.1.11694 /jair/2020/vougiouklis2020jair-point/

Abstract

We investigate the problem of generating natural language summaries from knowledge base triples. Our approach is based on a pointer-generator network, which, in addition to generating regular words from a fixed target vocabulary, is able to verbalise triples in several ways. We undertake an automatic and a human evaluation on single and open-domain summaries generation tasks. Both show that our approach significantly outperforms other data-driven baselines.

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Text

Vougiouklis et al. "Point at the Triple: Generation of Text Summaries from Knowledge Base Triples." Journal of Artificial Intelligence Research, 2020. doi:10.1613/JAIR.1.11694

Markdown

[Vougiouklis et al. "Point at the Triple: Generation of Text Summaries from Knowledge Base Triples." Journal of Artificial Intelligence Research, 2020.](https://mlanthology.org/jair/2020/vougiouklis2020jair-point/) doi:10.1613/JAIR.1.11694

BibTeX

@article{vougiouklis2020jair-point,
  title     = {{Point at the Triple: Generation of Text Summaries from Knowledge Base Triples}},
  author    = {Vougiouklis, Pavlos and Maddalena, Eddy and Hare, Jonathon S. and Simperl, Elena},
  journal   = {Journal of Artificial Intelligence Research},
  year      = {2020},
  pages     = {1-31},
  doi       = {10.1613/JAIR.1.11694},
  volume    = {69},
  url       = {https://mlanthology.org/jair/2020/vougiouklis2020jair-point/}
}