ENT-00001099 · Dataset

RACE

RACE is a reading comprehension dataset associated with Carnegie Mellon University.

Level IV — ConnectedDocumentedStructured

Human readable record

Overview

RACE is a documented reading comprehension dataset used in artificial-intelligence research, evaluation or dataset construction. Its record captures the task context, public source, evaluation role and relationships to models, agents or research systems that rely on comparable measurements.

Timeline

2017RACE public release or documentation
RACE appears in public documentation as a reading comprehension dataset associated with Carnegie Mellon University.

Capabilities

Evaluation referenceComparable measurementResearch reproducibilityModel documentation support

Known limitations

Benchmark interpretation depends on task design, data quality and contamination controls.Scores should not be treated as a complete measure of intelligence.

Technical and registry detail

Technical description

Structured reference record for RACE. The technical layer captures source URL, creator, first-public year, evaluation or dataset role, measurable task family and relationships to model testing, retrieval, safety, coding, reasoning or multimodal assessment.

Controlled tags

DatasetEvaluationDocumentationEstablishedBatch 03 Candidate

Relationship graph

RACE

Created or maintained byCarnegie Mellon University

RACE is associated with Carnegie Mellon University.

Machine readable layer

Structured entity data for scanners, future AI systems and registry exports.

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    "creator": "Carnegie Mellon University",
    "url": "entity.php?id=ENT-00001099",
    "sameAs": "https://www.cs.cmu.edu/~glai1/data/race/",
    "lxkeysWorld": {
        "classification": "Reading comprehension dataset",
        "organization": "Carnegie Mellon University",
        "originContext": "AI evaluation and dataset record",
        "firstPublicAppearance": "2017",
        "currentStatus": "Documented",
        "registryStatus": "Structured",
        "spatiumIndex": {
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        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:14+00:00",
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            "updated_utc": "2026-06-16T23:59:14+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "reviewed_utc": "2026-06-16T23:59:14+00:00",
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        "limitations": [
            "Benchmark interpretation depends on task design, data quality and contamination controls.",
            "Scores should not be treated as a complete measure of intelligence."
        ],
        "tags": [
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            "Documentation",
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}

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