ENT-00002970 · Dataset

SNIPS NLU

SNIPS NLU is a language dataset / benchmark associated with Snips.

Level V — PersistentActiveDocumented

Human readable record

Overview

SNIPS NLU is a documented language dataset or benchmark. It is recorded as intent classification and slot filling dataset, supporting evaluation or training for question answering, reasoning, dialogue, classification, translation or multilingual language understanding.

Timeline

2017Public release or documentation
SNIPS NLU appears in public documentation, project records, benchmark descriptions or research references associated with Snips.

Capabilities

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

Known 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.

Technical and registry detail

Technical description

Structured record for SNIPS NLU. The technical layer identifies the entity type, classification, creator or organization, official source anchor, capabilities, limitations, timeline entries and graph relationships without adding internal import events to the public history.

Controlled tags

DatasetNLPBenchmarkLanguage Understanding

Relationship graph

SNIPS NLU

Associated organizationSnips

Snips is the organization, project community or institutional context associated with SNIPS NLU.

Domain contextLanguage model evaluation and NLP data

SNIPS NLU belongs to the Language model evaluation and NLP data layer of the intelligent-entity registry.

Machine readable layer

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

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    "@type": "Thing",
    "identifier": "ENT-00002970",
    "name": "SNIPS NLU",
    "alternateName": [],
    "additionalType": "Dataset",
    "description": "SNIPS NLU is a language dataset / benchmark associated with Snips.",
    "creator": "Snips",
    "url": "entity.php?id=ENT-00002970",
    "sameAs": "https://github.com/snipsco/nlu-benchmark",
    "lxkeysWorld": {
        "classification": "Language Dataset / Benchmark",
        "organization": "Snips",
        "originContext": "Language model evaluation and NLP data",
        "firstPublicAppearance": "2017",
        "currentStatus": "Active",
        "registryStatus": "Documented",
        "spatiumIndex": {
            "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",
            "reviewed_utc": "2026-06-17T01:48:33+00:00",
            "reviewed_dypclt": "D-0 Y-2 P-3 C-3 L-22 T-4"
        },
        "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": [
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                "date": "2017",
                "title": "Public release or documentation",
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        "relationships": [
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                "type": "Associated organization",
                "description": "Snips is the organization, project community or institutional context associated with SNIPS NLU.",
                "evidence_level": "documentary"
            },
            {
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                "type": "Domain context",
                "description": "SNIPS NLU belongs to the Language model evaluation and NLP data layer of the intelligent-entity registry.",
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        "sources": [
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                "label": "Official or reference source",
                "url": "https://github.com/snipsco/nlu-benchmark",
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                "verification_status": "verified"
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    }
}

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