CO
ENT-00002938 · Jeu de données

CoQA

CoQA is a dataset associated with Stanford NLP, classified in LXKeys.world as Language / Training Dataset.

Niveau V PersistantActifDocumenté
Fiche publique

Vue d’ensemble

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

Chronologie

  1. 2018Initial dataset release

    CoQA entered the documented public record in 2018. 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 CoQA. Entity type: Dataset; classification: Language / Training Dataset; creator/organization context: Stanford NLP. Canonical source anchor: https://stanfordnlp.github.io/coqa/. 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

CoQA

Ouvrir dans le graphe complet
CoQA
Organisation associéeSortante
Stanford NLP

Stanford NLP is the organization, project community or institutional context associated with CoQA.

Contexte de domaineSortante
Language model evaluation and NLP data

CoQA 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": [
        "https://schema.org",
        {
            "lxw": "https://lxkeys.world/schema/"
        }
    ],
    "@type": "Thing",
    "identifier": "ENT-00002938",
    "name": "CoQA",
    "alternateName": [],
    "additionalType": {
        "category": "Data and Evaluation",
        "type": "Dataset",
        "subtype": "",
        "lxkeysEntity": false
    },
    "description": "CoQA is a dataset associated with Stanford NLP, classified in LXKeys.world as Language / Training Dataset.",
    "creator": "Stanford NLP",
    "url": "https://lxkeys.world/entry.php?id=ENT-00002938&lang=fr",
    "sameAs": "https://stanfordnlp.github.io/coqa/",
    "image": "",
    "lxkeysWorld": {
        "worldId": "ENT-00002938",
        "kind": "Data and Evaluation",
        "type": "Dataset",
        "subtype": "",
        "classification": "Language / Training Dataset",
        "organization": "Stanford NLP",
        "originContext": "Language model evaluation and NLP data",
        "firstPublicAppearance": "2018",
        "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": "2018",
                "title": "Initial dataset release",
                "description": "CoQA entered the documented public record in 2018. This event is retained at the precision supported by the Entry’s reviewed source history.",
                "source_url": "https://stanfordnlp.github.io/coqa/",
                "verification_status": "source_backed_official"
            }
        ],
        "relationships": [
            {
                "target": "Stanford NLP",
                "type": "Associated organization",
                "description": "Stanford NLP is the organization, project community or institutional context associated with CoQA.",
                "evidence_level": "documentary"
            },
            {
                "target": "Language model evaluation and NLP data",
                "type": "Domain context",
                "description": "CoQA 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://stanfordnlp.github.io/coqa/",
                "source_type": "Primary / Reference Source",
                "verification_status": "verified",
                "authority": "OFFICIAL",
                "role": "primary",
                "update_enabled": true,
                "authority_basis": "curated-corpus-refresh-2026-09-08"
            }
        ],
        "canonical": [],
        "imageMeta": []
    }
}
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