ENT-00002962 · Dataset

Civil Comments

Civil Comments is a language dataset / benchmark associated with Jigsaw / Conversation AI.

Level V — PersistentActiveDocumented

Human readable record

Overview

Civil Comments is a documented language dataset or benchmark. It is recorded as toxicity and identity comment dataset, supporting evaluation or training for question answering, reasoning, dialogue, classification, translation or multilingual language understanding.

Timeline

2019Public release or documentation
Civil Comments appears in public documentation, project records, benchmark descriptions or research references associated with Jigsaw / Conversation AI.

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 Civil Comments. 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

Civil Comments

Associated organizationJigsaw / Conversation AI

Jigsaw / Conversation AI is the organization, project community or institutional context associated with Civil Comments.

Domain contextLanguage model evaluation and NLP data

Civil Comments 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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    "@context": "https://schema.org",
    "@type": "Thing",
    "identifier": "ENT-00002962",
    "name": "Civil Comments",
    "alternateName": [],
    "additionalType": "Dataset",
    "description": "Civil Comments is a language dataset / benchmark associated with Jigsaw / Conversation AI.",
    "creator": "Jigsaw / Conversation AI",
    "url": "entity.php?id=ENT-00002962",
    "sameAs": "https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification",
    "lxkeysWorld": {
        "classification": "Language Dataset / Benchmark",
        "organization": "Jigsaw / Conversation AI",
        "originContext": "Language model evaluation and NLP data",
        "firstPublicAppearance": "2019",
        "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": [
            {
                "date": "2019",
                "title": "Public release or documentation",
                "description": "Civil Comments appears in public documentation, project records, benchmark descriptions or research references associated with Jigsaw / Conversation AI."
            }
        ],
        "relationships": [
            {
                "target": "Jigsaw / Conversation AI",
                "type": "Associated organization",
                "description": "Jigsaw / Conversation AI is the organization, project community or institutional context associated with Civil Comments.",
                "evidence_level": "documentary"
            },
            {
                "target": "Language model evaluation and NLP data",
                "type": "Domain context",
                "description": "Civil Comments 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://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification",
                "source_type": "Primary / Reference Source",
                "verification_status": "verified"
            }
        ]
    }
}

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