demonstration

NaLIR: an interactive natural language interface for querying relational databases

Authors:

Fei Li,

Hosagrahar V JagadishAuthors Info & Claims

SIGMOD '14: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data

Pages 709 - 712

https://doi.org/10.1145/2588555.2594519

Published: 18 June 2014 Publication History

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Abstract

In this demo, we present NaLIR, a generic interactive natural language interface for querying relational databases. NaLIR can accept a logically complex English language sentence as query input. This query is first translated into a SQL query, which may include aggregation, nesting, and various types of joins, among other things, and then evaluated against an RDBMS. In this demonstration, we show that NaLIR, while far from being able to pass the Turing test, is perfectly usable in practice, and able to handle even quite complex queries in a variety of application domains. In addition, we also demonstrate how carefully designed interactive communication can avoid misinterpretation with minimum user burden.

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Cited By

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Trummer I(2024)Generating Succinct Descriptions of Database Schemata for Cost-Efficient Prompting of Large Language ModelsProceedings of the VLDB Endowment10.14778/3681954.368201717:11(3511-3523)Online publication date: 30-Aug-2024
https://doi.org/10.14778/3681954.3682017
Li BLuo YChai CLi GTang N(2024)The Dawn of Natural Language to SQL: Are We Fully Ready?Proceedings of the VLDB Endowment10.14778/3681954.368200317:11(3318-3331)Online publication date: 30-Aug-2024
https://doi.org/10.14778/3681954.3682003
Tian YKummerfeld JLi TZhang T(2024)SQLucid: Grounding Natural Language Database Queries with Interactive ExplanationsProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676368(1-20)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676368
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Index Terms

NaLIR: an interactive natural language interface for querying relational databases
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Natural language interfaces

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Information & Contributors

Information

Published In

SIGMOD '14: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data

June 2014

1645 pages

ISBN:9781450323765

DOI:10.1145/2588555

General Chairs:
Curtis Dyreson
Utah State University, USA
,
Feifei Li
University of Utah, USA
,
Program Chair:
M. Tamer Özsu
University of Waterloo, Canada

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 June 2014

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Demonstration

Funding Sources

Division of Information and Intelligent Systems

Conference

SIGMOD/PODS'14

Sponsor:

SIGMOD

SIGMOD/PODS'14: International Conference on Management of Data

June 22 - 27, 2014

Utah, Snowbird, USA

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SIGMOD '14 Paper Acceptance Rate 107 of 421 submissions, 25%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

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https://doi.org/10.14778/3681954.3682017
Li BLuo YChai CLi GTang N(2024)The Dawn of Natural Language to SQL: Are We Fully Ready?Proceedings of the VLDB Endowment10.14778/3681954.368200317:11(3318-3331)Online publication date: 30-Aug-2024
https://doi.org/10.14778/3681954.3682003
Tian YKummerfeld JLi TZhang T(2024)SQLucid: Grounding Natural Language Database Queries with Interactive ExplanationsProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676368(1-20)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676368
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