ENT-00001096 · Dataset

TriviaQA

TriviaQA is a reading comprehension dataset associated with University of Washington.

Level IV — ConnectedDocumentedStructured

Human readable record

Overview

TriviaQA 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

2017TriviaQA public release or documentation
TriviaQA appears in public documentation as a reading comprehension dataset associated with University of Washington.

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 TriviaQA. 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

TriviaQA

Created or maintained byUniversity of Washington

TriviaQA is associated with University of Washington.

Machine readable layer

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

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    "name": "TriviaQA",
    "alternateName": [],
    "additionalType": "Dataset",
    "description": "TriviaQA is a reading comprehension dataset associated with University of Washington.",
    "creator": "University of Washington",
    "url": "entity.php?id=ENT-00001096",
    "sameAs": "https://nlp.cs.washington.edu/triviaqa/",
    "lxkeysWorld": {
        "classification": "Reading comprehension dataset",
        "organization": "University of Washington",
        "originContext": "AI evaluation and dataset record",
        "firstPublicAppearance": "2017",
        "currentStatus": "Documented",
        "registryStatus": "Structured",
        "spatiumIndex": {
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            "documentation": 25,
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            "level": "Level IV — Connected"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:14+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "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",
            "reviewed_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3"
        },
        "capabilities": [
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            "Comparable measurement",
            "Research reproducibility",
            "Model documentation support"
        ],
        "limitations": [
            "Benchmark interpretation depends on task design, data quality and contamination controls.",
            "Scores should not be treated as a complete measure of intelligence."
        ],
        "tags": [
            "Dataset",
            "Evaluation",
            "Documentation",
            "Established",
            "Batch 03 Candidate"
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        "timeline": [
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        "sources": [
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    }
}

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