Datasets › SQA

SQA (SequentialQA)

Introduced by Mohit Iyyer et al. in Search-based Neural Structured Learning for Sequential Question Answering1 Jul 2017 archive 2025-07-28

The SQA dataset was created to explore the task of answering sequences of inter-related questions on HTML tables. It has 6,066 sequences with 17,553 questions in total.

Source: SQA

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
Semantic Parsing SQA TAPEX-Large Denotation Accuracy 74.5 TAPEX: Table Pre-training via Learning a Neural SQL Executor microsoft/Table-Pretraining +3 2 Compare

Papers archive 2025-07-28

2 shown of 2 papers 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 37. 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
TAPEX: Table Pre-training via Learning a Neural SQL Executor 4 1 16 Jul 2021 not harvested
TAPAS: Weakly Supervised Table Parsing via Pre-training 8 1 5 Apr 2020 ran 0 of 14 samples (14 unverified)

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • SQA

1 variant name, as the archive lists them.

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