ENT-00001936 · AI Dataset

TextVQA

TextVQA is a visual question answering dataset associated with Research community.

Level IV — ConnectedActiveDocumented

Human readable record

Overview

TextVQA is a documented AI dataset or benchmark associated with Research community. The record identifies its role in evaluation, training, measurement or comparison of intelligent systems, with emphasis on the source context and the type of capability it helps assess.

Timeline

2019TextVQA public documentation anchor
TextVQA appears in public documentation or stable reference sources as a visual question answering dataset associated with Research community.

Capabilities

Data resourceEvaluation supportResearch reference

Known limitations

The record describes the public identity and documented role of the entity, not private implementation details.Capabilities depend on version, deployment context, access conditions and the available public documentation.

Technical and registry detail

Technical description

Structured record for TextVQA. The technical layer identifies entity type, classification, creator or organization, public source anchors, timeline entry, capabilities, limitations, registry status and graph relationships. Source anchor: https://textvqa.org/.

Controlled tags

DatasetBenchmarkEvaluation

Relationship graph

TextVQA

Published byResearch community

TextVQA is associated with Research community through its documented source context.

Machine readable layer

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

{
    "@context": "https://schema.org",
    "@type": "Thing",
    "identifier": "ENT-00001936",
    "name": "TextVQA",
    "alternateName": [],
    "additionalType": "AI Dataset",
    "description": "TextVQA is a visual question answering dataset associated with Research community.",
    "creator": "TextVQA authors",
    "url": "entity.php?id=ENT-00001936",
    "sameAs": "https://textvqa.org",
    "lxkeysWorld": {
        "classification": "visual question answering dataset",
        "organization": "Research community",
        "originContext": "Public AI and technical record",
        "firstPublicAppearance": "2019",
        "currentStatus": "Active",
        "registryStatus": "Documented",
        "spatiumIndex": {
            "total": 74,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 11,
            "level": "Level IV — Connected"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:29+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:29+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "reviewed_utc": "2026-06-16T23:59:29+00:00",
            "reviewed_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3"
        },
        "capabilities": [
            "Data resource",
            "Evaluation support",
            "Research reference"
        ],
        "limitations": [
            "The record describes the public identity and documented role of the entity, not private implementation details.",
            "Capabilities depend on version, deployment context, access conditions and the available public documentation."
        ],
        "tags": [
            "Dataset",
            "Benchmark",
            "Evaluation"
        ],
        "timeline": [
            {
                "date": "2019",
                "title": "TextVQA public documentation anchor",
                "description": "TextVQA appears in public documentation or stable reference sources as a visual question answering dataset associated with Research community."
            }
        ],
        "relationships": [
            {
                "target": "Research community",
                "type": "Published by",
                "description": "TextVQA is associated with Research community through its documented source context.",
                "evidence_level": "documentary"
            }
        ],
        "sources": [
            {
                "label": "TextVQA site",
                "url": "https://textvqa.org/",
                "source_type": "Official Documentation",
                "verification_status": "verified"
            }
        ]
    }
}

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