ENT-00001683 · AI Dataset

MLQA

MLQA is a multilingual question answering dataset associated with Meta AI.

Level IV — ConnectedActiveDocumented

Human readable record

Overview

MLQA is a documented AI dataset or benchmark associated with Meta AI. 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

2019MLQA public documentation anchor
MLQA appears in public documentation or stable reference sources as a multilingual question answering dataset associated with Meta AI.

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 MLQA. 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://github.com/facebookresearch/MLQA.

Controlled tags

DatasetBenchmarkEvaluation

Relationship graph

MLQA

Published byMeta AI

MLQA is associated with Meta AI through its documented source context.

Machine readable layer

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

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    "@context": "https://schema.org",
    "@type": "Thing",
    "identifier": "ENT-00001683",
    "name": "MLQA",
    "alternateName": [],
    "additionalType": "AI Dataset",
    "description": "MLQA is a multilingual question answering dataset associated with Meta AI.",
    "creator": "Facebook AI Research",
    "url": "entity.php?id=ENT-00001683",
    "sameAs": "https://github.com/facebookresearch/MLQA",
    "lxkeysWorld": {
        "classification": "multilingual question answering dataset",
        "organization": "Meta AI",
        "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": "2026-06-16T23:59:28+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:28+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "reviewed_utc": "2026-06-16T23:59:28+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": "MLQA public documentation anchor",
                "description": "MLQA appears in public documentation or stable reference sources as a multilingual question answering dataset associated with Meta AI."
            }
        ],
        "relationships": [
            {
                "target": "Meta AI",
                "type": "Published by",
                "description": "MLQA is associated with Meta AI through its documented source context.",
                "evidence_level": "documentary"
            }
        ],
        "sources": [
            {
                "label": "Official dataset or benchmark reference",
                "url": "https://github.com/facebookresearch/MLQA",
                "source_type": "Official Repository",
                "verification_status": "verified"
            }
        ]
    }
}

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