Sign inGet started
Dataset · Hugging Face

microsoft/msr_sqa

Recent work in semantic parsing for question answering has focused on long and complicated questions, many of which would seem unnatural if asked in a normal conversation between two humans. In an effort to explore a conversational QA setting, we present a more realistic task: answering sequences of simple but inter-related questions. We created SQA by asking crowdsourced workers to decompose 2,022 questions from WikiTableQuestions (WTQ), which contains highly-compositional questions about tables from Wikipedia. We had three workers decompose each WTQ question, resulting in a dataset of 6,066

Author / organizationmicrosoft
License (as declared)ms-pl
Downloads284 (as reported by Hugging Face)
Likes8
Created2 March 2022
Last updated at source18 January 2024
Embed this entry
<iframe src="https://silytics.si/embed/item/dd5b8574-89c9-48f1-a825-ddc8b89718db" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 2 days

284 now (+6 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.

More from microsoft

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.