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A text dataset of typed decision examples in parquet format, sized 1M to 10M rows. Rows carry state, question, target distribution, and provenance fields drawn from sources like MedQA and procedural rule-firing tasks.
- Reading time
- 1 min
- Published by
- Community
- Added
- Oct 2026
Highlights
- Text modality, parquet format, 1M to 10M rows
- Rows include state_json, question_json, target_distribution_json, and provenance_json
- Sources include MedQA-USMLE-4-options-hf and procedural-typed-decisions event_triggered_execution
- Per-row provenance records license, source split, and upstream example ID
- Usable with Datasets, Dask, and Polars libraries
Questions about this entry
Short answers drawn from the linked project or page.
It is a Hugging Face text dataset of typed decision examples stored as parquet, sized between 1M and 10M rows. Each row pairs a state with a question and a target distribution.
Rows carry id, source, category, group, state_json, question_json, target_distribution_json, provenance_json, sequence_upper_bound, and source_split.
Question types include choice, as in the MedQA-USMLE-4-options rows, and score, as in the procedural rule-firing rows asking how many firings occur in total.
Licenses vary per row and are recorded in provenance_json. Examples include apache-2.0 for the procedural rule-firing rows and cc-by-sa-4.0 for the MedQA rows.
The dataset card lists Datasets, Dask, and Polars among the supported libraries.
Sources include MedQA-USMLE-4-options-hf and procedural-typed-decisions/event_triggered_execution, with provenance recording the source split and upstream example ID for each row.
Because licenses vary per source and some rows carry share-alike terms, check provenance_json before commercial use rather than assuming a single dataset-wide license.
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