NLProv: Natural language provenance

Daniel Deutch, Nave Frost, Amir Gilad

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations

Abstract

We propose to present NLProv: an end-to-end Natural Language (NL) interface for database queries. Previous work has focused on interfaces for specifying NL questions, which are then compiled into queries in a formal language (e.g. SQL). We build upon this work, but focus on presenting a detailed form of the answers in Natural Language. The answers that we present are importantly based on the provenance of tuples in the query result, detailing not only which are the results but also their explanations. We develop a novel method for transforming provenance information to NL, by leveraging the original NL question structure. Furthermore, since provenance information is typically large, we present two solutions for its effective presentation as NL text: one that is based on provenance factorization with novel desiderata relevant to the NL case, and one that is based on summarization.

Original languageEnglish
Pages (from-to)1537-1540
Number of pages4
JournalProceedings of the VLDB Endowment
Volume9
Issue number13
DOIs
StatePublished - 2015
Event42nd International Conference on Very Large Data Bases, VLDB 2016 - New Delhi, India
Duration: 5 Sep 20169 Sep 2016

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