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Dataset research report

Social I Qa research report

A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.

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Executive Summary

We introduce Social IQa: Social Interaction QA, a new question-answering benchmark for testing social commonsense intelligence. Contrary to many prior benchmarks that focus on physical or taxonomic knowledge, Social IQa focuses on reasoning about people’s actions and their social implications. For example, given an action like "Jesse saw a concert" and a question like "Why did Jesse do this?", humans can easily infer that Jesse wanted "to see their favorite performer" or "to enjoy the music", and not "to see what's happening inside" or "to see if it works". The actions in Social IQa span a wide variety of social situations, and answer candidates contain both human-curated answers and adversarially-filtered machine-generated candidates. Social IQa contains over 37,000 QA pairs for evaluatin…

Finding 1The dataset has unknown rows available in the catalog.
Finding 2The catalog exposes 0 documented or inferred columns.
Finding 3Helix has 3 ready query prompts for this dataset.
Finding 4This report still exposes schema, preview rows, and query prompts even when charts cannot be precomputed.

Follow-Up Queries

Method And Limits

  • Load the catalog entry and preview rows from the processed dataset file.
  • Infer numeric, categorical, time, and location fields from real columns.
  • Generate a small set of defensive Plotly chart specifications from that profile.
  • Expose each chart idea as a query link so the report can be rerun or exported in Helix.

This report is intentionally reproducible. It uses the local catalog metadata and generated chart specifications rather than claiming external conclusions beyond the dataset.

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