Real Life Application of a Question Answering System Using BERT Language Model

Francesca Alloatti, Luigi Di Caro, Gianpiero Sportelli

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Abstract
It is often hard to apply the newest advances in research to real life scenarios. They usually require the resolution of some specific task applied to a restricted domain, all the while providing small amounts of data to begin with. In this study we apply one of the newest innovations in Deep Learning to a task of text classification. We created a question answering system in Italian that provides information about a specific subject, e-invoicing and digital billing. Italy recently introduced a new legislation about e-invoicing and people have some legit doubts, therefore a large share of professionals could benefit from this tool.
Anthology ID:
W19-5930
Volume:
Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue
Month:
September
Year:
2019
Address:
Stockholm, Sweden
Editors:
Satoshi Nakamura, Milica Gasic, Ingrid Zukerman, Gabriel Skantze, Mikio Nakano, Alexandros Papangelis, Stefan Ultes, Koichiro Yoshino
Venue:
SIGDIAL
SIG:
SIGDIAL
Publisher:
Association for Computational Linguistics
Note:
Pages:
250–253
Language:
URL:
https://aclanthology.org/W19-5930
DOI:
10.18653/v1/W19-5930
Bibkey:
Cite (ACL):
Francesca Alloatti, Luigi Di Caro, and Gianpiero Sportelli. 2019. Real Life Application of a Question Answering System Using BERT Language Model. In Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue, pages 250–253, Stockholm, Sweden. Association for Computational Linguistics.
Cite (Informal):
Real Life Application of a Question Answering System Using BERT Language Model (Alloatti et al., SIGDIAL 2019)
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PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/W19-5930.pdf
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