MU
ENT-00002832 · Benchmark

MultiPL-E

MultiPL-E is a AI benchmark associated with MultiPL-E contributors, classified in LXKeys.world as AI Benchmark / Evaluation.

Niveau V PersistantActifDocumenté
Fiche publique

Vue d’ensemble

MultiPL-E is a documented benchmark or dataset used to evaluate code intelligence, program synthesis, debugging, semantic parsing or data reasoning. It is recorded as multilingual programming benchmark.

Chronologie

  1. 2022Initial benchmark release

    MultiPL-E entered the documented public record in 2022. This event is retained at the precision supported by the Entry’s reviewed source history.

Capacités

Evaluation protocol documentationModel comparison supportTask taxonomy mappingReproducible benchmark anchoringRelationship graph compatibility

Limites connues

Benchmark results can become stale as models improve and evaluation protocols evolve.A benchmark measures a defined task scope rather than complete intelligence.
Détail technique et structuré

Description technique

Structured LXKeys.world registry record for MultiPL-E. Entity type: Benchmark; classification: AI Benchmark / Evaluation; creator/organization context: MultiPL-E contributors. Canonical source anchor: https://github.com/nuprl/MultiPL-E. The record tracks source authority, first public appearance, timeline, capabilities, limitations, registry status and graph relationships. Automatic refresh is limited to sources explicitly classified as OFFICIAL and enabled for updates; documentary and research references remain non-authoritative unless reviewed.

Tags contrôlés

BenchmarkCode IntelligenceSoftware EngineeringEvaluation
Graphe relationnel

MultiPL-E

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MultiPL-E
Organisation associéeSortante
MultiPL-E contributors

MultiPL-E contributors is the organization, project community or institutional context associated with MultiPL-E.

Contexte de domaineSortante
Code and data reasoning evaluation

MultiPL-E belongs to the Code and data reasoning evaluation layer of the intelligent-entity registry.

Couche lisible par machine

Données structurées de l’entrée pour les outils humains, les systèmes IA et les clients machine.

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    "@context": [
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        {
            "lxw": "https://lxkeys.world/schema/"
        }
    ],
    "@type": "Thing",
    "identifier": "ENT-00002832",
    "name": "MultiPL-E",
    "alternateName": [],
    "additionalType": {
        "category": "Data and Evaluation",
        "type": "Benchmark",
        "subtype": "",
        "lxkeysEntity": false
    },
    "description": "MultiPL-E is a AI benchmark associated with MultiPL-E contributors, classified in LXKeys.world as AI Benchmark / Evaluation.",
    "creator": "MultiPL-E contributors",
    "url": "https://lxkeys.world/entry.php?id=ENT-00002832&lang=fr",
    "sameAs": "https://github.com/nuprl/MultiPL-E",
    "image": "",
    "lxkeysWorld": {
        "worldId": "ENT-00002832",
        "kind": "Data and Evaluation",
        "type": "Benchmark",
        "subtype": "",
        "classification": "AI Benchmark / Evaluation",
        "organization": "MultiPL-E contributors",
        "originContext": "Code and data reasoning evaluation",
        "firstPublicAppearance": "2022",
        "currentStatus": "Active",
        "documentationStatus": "Documented",
        "documentationIndex": {
            "total": 82,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 19,
            "level": "Level V Persistent"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-17T01:48:33+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-22 T-4",
            "updated_utc": "2026-06-17T01:48:33+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-22 T-4"
        },
        "facts": [],
        "capabilities": [
            "Evaluation protocol documentation",
            "Model comparison support",
            "Task taxonomy mapping",
            "Reproducible benchmark anchoring",
            "Relationship graph compatibility"
        ],
        "limitations": [
            "Benchmark results can become stale as models improve and evaluation protocols evolve.",
            "A benchmark measures a defined task scope rather than complete intelligence."
        ],
        "tags": [
            "Benchmark",
            "Code Intelligence",
            "Software Engineering",
            "Evaluation"
        ],
        "timeline": [
            {
                "date": "2022",
                "title": "Initial benchmark release",
                "description": "MultiPL-E entered the documented public record in 2022. This event is retained at the precision supported by the Entry’s reviewed source history.",
                "source_url": "https://github.com/nuprl/MultiPL-E",
                "verification_status": "source_backed_curated_baseline"
            }
        ],
        "relationships": [
            {
                "target": "MultiPL-E contributors",
                "type": "Associated organization",
                "description": "MultiPL-E contributors is the organization, project community or institutional context associated with MultiPL-E.",
                "evidence_level": "documentary"
            },
            {
                "target": "Code and data reasoning evaluation",
                "type": "Domain context",
                "description": "MultiPL-E belongs to the Code and data reasoning evaluation layer of the intelligent-entity registry.",
                "evidence_level": "documentary"
            }
        ],
        "sources": [
            {
                "label": "Official or reference source",
                "url": "https://github.com/nuprl/MultiPL-E",
                "source_type": "Research Source",
                "verification_status": "verified",
                "authority": "TRUSTED_PRIMARY",
                "role": "code_repository",
                "update_enabled": false,
                "authority_basis": "curated-corpus-refresh-2026-09-08"
            }
        ],
        "canonical": [],
        "imageMeta": []
    }
}
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