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Netted?! How to Improve the Usefulness of Spider & Co.

Hättasch, Benjamin ; Geisler, Nadja ; Binnig, Carsten (2021)
Netted?! How to Improve the Usefulness of Spider & Co.
2nd International Biennial Conference on Design of Experimental Search & Information Retrieval Systems (DESIRES 2021). Padua, Italy (15.-18.09.2021)
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Natural language interfaces for databases (NLIDBs) are an intuitive way to access and explore structured data. That makes challenges like Spider (Yale’s semantic parsing and text-to-SQL challenge) valuable, as they produce a series of approaches for NL-to-SQL-translation. However, the resulting contributions leave something to be desired. In this paper, we analyze the usefulness of those submissions to the leaderboard for future research. We also present a prototypical implementation called UniverSQL that makes these approaches easier to use in information access systems. We hope that this lowered barrier encourages (future) participants of these challenges to add support for actual usage of their submissions. Finally, we discuss what could be done to improve future benchmarks and shared tasks for (not only) NLIDBs.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2021
Autor(en): Hättasch, Benjamin ; Geisler, Nadja ; Binnig, Carsten
Art des Eintrags: Bibliographie
Titel: Netted?! How to Improve the Usefulness of Spider & Co.
Sprache: Englisch
Publikationsjahr: 15 September 2021
Veranstaltungstitel: 2nd International Biennial Conference on Design of Experimental Search & Information Retrieval Systems (DESIRES 2021)
Veranstaltungsort: Padua, Italy
Veranstaltungsdatum: 15.-18.09.2021
URL / URN: https://http://desires.dei.unipd.it/
Kurzbeschreibung (Abstract):

Natural language interfaces for databases (NLIDBs) are an intuitive way to access and explore structured data. That makes challenges like Spider (Yale’s semantic parsing and text-to-SQL challenge) valuable, as they produce a series of approaches for NL-to-SQL-translation. However, the resulting contributions leave something to be desired. In this paper, we analyze the usefulness of those submissions to the leaderboard for future research. We also present a prototypical implementation called UniverSQL that makes these approaches easier to use in information access systems. We hope that this lowered barrier encourages (future) participants of these challenges to add support for actual usage of their submissions. Finally, we discuss what could be done to improve future benchmarks and shared tasks for (not only) NLIDBs.

Freie Schlagworte: dm, dm_nhr4ces, dm_aiphes, dm_softwarecampus, dm_project_AIPHES_area_d2, dm_project_wannadb
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Data Management (2022 umbenannt in Data and AI Systems)
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen
Hinterlegungsdatum: 10 Dez 2021 09:29
Letzte Änderung: 10 Dez 2021 09:29
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