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TempQA-WD

Introduced by Sumit Neelam et al. in A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases15 Jan 2022 archive 2025-07-28

TempQA-WD is a benchmark dataset for temporal reasoning designed to encourage research in extending the present approaches to target a more challenging set of complex reasoning tasks. Specifically, the benchmark is a temporal question answering dataset with the following advantages: (a) it is based on Wikidata, which is the most frequently curated, openly available knowledge base, (b) it includes intermediate sparql queries to facilitate the evaluation of semantic parsing based approaches for KBQA, and (c) it generalizes to multiple knowledge bases: Freebase and Wikidata.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Question Answering TempQA-WD BestOfBoth F1 41.6 — — 2 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 2. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases 0 1 28 Sep 2021 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Creative Commons Zero v1.0 Universal

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • TempQA-WD

1 variant name, as the archive lists them.

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