LO
ENT-00002947 · Jeu de données

LogiQA

LogiQA is a dataset associated with LogiQA contributors, classified in LXKeys.world as Language / Training Dataset.

Niveau V PersistantActifDocumenté
Fiche publique

Vue d’ensemble

LogiQA is a documented language dataset or benchmark. It is recorded as logical reasoning question answering dataset, supporting evaluation or training for question answering, reasoning, dialogue, classification, translation or multilingual language understanding.

Chronologie

  1. 2020Initial dataset release

    LogiQA entered the documented public record in 2020. This event is retained at the precision supported by the Entry’s reviewed source history.

Capacités

Dataset referenceBenchmark or training-data contextTask-level documentationModel evaluation supportSource-based traceability

Limites connues

Dataset coverage, licensing, annotation quality and benchmark relevance depend on the source version and use context.Performance claims should be assessed through models evaluated on the dataset rather than inferred from the dataset alone.
Détail technique et structuré

Description technique

Structured LXKeys.world registry record for LogiQA. Entity type: Dataset; classification: Language / Training Dataset; creator/organization context: LogiQA contributors. Canonical source anchor: https://github.com/lgw863/LogiQA-dataset. 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

DatasetNLPBenchmarkLanguage Understanding
Graphe relationnel

LogiQA

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LogiQA
Organisation associéeSortante
LogiQA contributors

LogiQA contributors is the organization, project community or institutional context associated with LogiQA.

Contexte de domaineSortante
Language model evaluation and NLP data

LogiQA belongs to the Language model evaluation and NLP data 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.

{
    "@context": [
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        {
            "lxw": "https://lxkeys.world/schema/"
        }
    ],
    "@type": "Thing",
    "identifier": "ENT-00002947",
    "name": "LogiQA",
    "alternateName": [],
    "additionalType": {
        "category": "Data and Evaluation",
        "type": "Dataset",
        "subtype": "",
        "lxkeysEntity": false
    },
    "description": "LogiQA is a dataset associated with LogiQA contributors, classified in LXKeys.world as Language / Training Dataset.",
    "creator": "LogiQA contributors",
    "url": "https://lxkeys.world/entry.php?id=ENT-00002947&lang=fr",
    "sameAs": "https://github.com/lgw863/LogiQA-dataset",
    "image": "",
    "lxkeysWorld": {
        "worldId": "ENT-00002947",
        "kind": "Data and Evaluation",
        "type": "Dataset",
        "subtype": "",
        "classification": "Language / Training Dataset",
        "organization": "LogiQA contributors",
        "originContext": "Language model evaluation and NLP data",
        "firstPublicAppearance": "2020",
        "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": [
            "Dataset reference",
            "Benchmark or training-data context",
            "Task-level documentation",
            "Model evaluation support",
            "Source-based traceability"
        ],
        "limitations": [
            "Dataset coverage, licensing, annotation quality and benchmark relevance depend on the source version and use context.",
            "Performance claims should be assessed through models evaluated on the dataset rather than inferred from the dataset alone."
        ],
        "tags": [
            "Dataset",
            "NLP",
            "Benchmark",
            "Language Understanding"
        ],
        "timeline": [
            {
                "date": "2020",
                "title": "Initial dataset release",
                "description": "LogiQA entered the documented public record in 2020. This event is retained at the precision supported by the Entry’s reviewed source history.",
                "source_url": "https://github.com/lgw863/LogiQA-dataset",
                "verification_status": "source_backed_curated_baseline"
            }
        ],
        "relationships": [
            {
                "target": "LogiQA contributors",
                "type": "Associated organization",
                "description": "LogiQA contributors is the organization, project community or institutional context associated with LogiQA.",
                "evidence_level": "documentary"
            },
            {
                "target": "Language model evaluation and NLP data",
                "type": "Domain context",
                "description": "LogiQA belongs to the Language model evaluation and NLP data layer of the intelligent-entity registry.",
                "evidence_level": "documentary"
            }
        ],
        "sources": [
            {
                "label": "Official or reference source",
                "url": "https://github.com/lgw863/LogiQA-dataset",
                "source_type": "Primary / Reference 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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