Explaining queries over web tables to non-experts

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Designing a reliable natural language (NL) interface for querying tables has been a longtime goal of researchers in both the data management and natural language processing (NLP) communities. Such an interface receives as input an NL question, translates it into a formal query, executes the query and returns the results. Errors in the translation process are not uncommon, and users typically struggle to understand whether their query has been mapped correctly. We address this problem by explaining the obtained formal queries to non-expert users. We introduce novel query explanations that provide a graphic representation of the query cell-based provenance (in its execution on a given table). Our solution augments a state-of-the-art NL interface over web tables, enhancing it in both its training and deployment phase. Experiments, including a user study conducted on Amazon Mechanical Turk, show our solution to improve both the correctness and reliability of the NL interface.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)9781538674741
StatePublished - Apr 2019
Event35th IEEE International Conference on Data Engineering, ICDE 2019 - Macau, China
Duration: 8 Apr 201911 Apr 2019

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627


Conference35th IEEE International Conference on Data Engineering, ICDE 2019


  • Annotations
  • Natural language processing
  • Nl interfaces
  • Nlp
  • Provenance
  • Query explanations
  • Semantic parsing
  • Weak supervision


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