QuTE: Answering Quantity Queries from Web Tables

Summary: QuTE extracts entity–quantity facts from web tables and supports online processing of quantity queries. It presents new query-matching and answer-ranking techniques for quantity filters, bridging the web-table data with structured KBs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6107
Venue: SIGMOD
Year: 2021
Pagerank: 5.351298e-05
Overall Rank: 8,886 | 39.04%
DOI: 10.1145/3448016.3452763

Incoming Non-self Citations Over Time

Authors

1. Vinh Thinh Ho (Max Planck Institute)
2. Koninika Pal (Max Planck Institute)
3. Gerhard Weikum (Max Planck Institute)

BibTeX Citation

@inproceedings{ho_sigmod21,
        title = {{QuTE: Answering Quantity Queries from Web Tables}},
        author = {Ho, Vinh Thinh and Pal, Koninika and Weikum, Gerhard},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3452763},
        url = {https://dl.acm.org/doi/10.1145/3448016.3452763},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,315	SANTOS: Relationship-based Semantic Table Union Search	2023	SIGMOD	8.7605101e-05
4,687	Knowledge Graphs 2021: A Data Odyssey	2021	VLDB	6.5620198e-05

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
317	Annotating and Searching Web Tables Using Entities, Types and Relationships	2010	VLDB	0.00021402049
3,271	Ten Years of WebTables	2018	VLDB	7.5779937e-05

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