ENT-00001130 · Dataset

VQAv2

VQAv2 is a visual question answering dataset associated with VQA authors.

Level IV — ConnectedDocumentedStructured

Human readable record

Overview

VQAv2 is a documented visual question answering 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

2017VQAv2 public release or documentation
VQAv2 appears in public documentation as a visual question answering dataset associated with VQA authors.

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 VQAv2. 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

VQAv2

Created or maintained byVQA authors

VQAv2 is associated with VQA authors.

Machine readable layer

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

{
    "@context": "https://schema.org",
    "@type": "Thing",
    "identifier": "ENT-00001130",
    "name": "VQAv2",
    "alternateName": [],
    "additionalType": "Dataset",
    "description": "VQAv2 is a visual question answering dataset associated with VQA authors.",
    "creator": "VQA authors",
    "url": "entity.php?id=ENT-00001130",
    "sameAs": "https://visualqa.org/",
    "lxkeysWorld": {
        "classification": "Visual question answering dataset",
        "organization": "VQA authors",
        "originContext": "AI evaluation and dataset record",
        "firstPublicAppearance": "2017",
        "currentStatus": "Documented",
        "registryStatus": "Structured",
        "spatiumIndex": {
            "total": 74,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 11,
            "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": [
            "Evaluation reference",
            "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"
        ],
        "timeline": [
            {
                "date": "2017",
                "title": "VQAv2 public release or documentation",
                "description": "VQAv2 appears in public documentation as a visual question answering dataset associated with VQA authors."
            }
        ],
        "relationships": [
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                "target": "VQA authors",
                "type": "Created or maintained by",
                "description": "VQAv2 is associated with VQA authors.",
                "evidence_level": "documentary"
            }
        ],
        "sources": [
            {
                "label": "VQAv2 public reference",
                "url": "https://visualqa.org/",
                "source_type": "Primary or Research Source",
                "verification_status": "verified"
            }
        ]
    }
}

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