ENT-00001080 · Dataset

MBPP

MBPP is a mostly basic python problems associated with Google Research.

Level IV — ConnectedActiveStructured

Human readable record

Overview

MBPP is a documented mostly basic python problems used in artificial-intelligence research, evaluation or dataset construction. Its record captures the task context, public source, evaluation role and relationships to models, agents or research systems that rely on comparable measurements.

Timeline

2021MBPP public release or documentation
MBPP appears in public documentation as a mostly basic python problems associated with Google Research.

Capabilities

Evaluation referenceComparable measurementResearch reproducibilityModel documentation support

Known limitations

Benchmark interpretation depends on task design, data quality and contamination controls.Scores should not be treated as a complete measure of intelligence.

Technical and registry detail

Technical description

Structured reference record for MBPP. The technical layer captures source URL, creator, first-public year, evaluation or dataset role, measurable task family and relationships to model testing, retrieval, safety, coding, reasoning or multimodal assessment.

Controlled tags

DatasetEvaluationDocumentationContemporaryBatch 03 Candidate

Relationship graph

MBPP

Created or maintained byGoogle Research

MBPP is associated with Google Research.

Machine readable layer

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

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    "identifier": "ENT-00001080",
    "name": "MBPP",
    "alternateName": [],
    "additionalType": "Dataset",
    "description": "MBPP is a mostly basic python problems associated with Google Research.",
    "creator": "Google Research",
    "url": "entity.php?id=ENT-00001080",
    "sameAs": "https://github.com/google-research/google-research/tree/master/mbpp",
    "lxkeysWorld": {
        "classification": "Mostly Basic Python Problems",
        "organization": "Google Research",
        "originContext": "AI evaluation and dataset record",
        "firstPublicAppearance": "2021",
        "currentStatus": "Active",
        "registryStatus": "Structured",
        "spatiumIndex": {
            "total": 74,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 11,
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        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:14+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:14+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "reviewed_utc": "2026-06-16T23:59:14+00:00",
            "reviewed_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3"
        },
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            "Comparable measurement",
            "Research reproducibility",
            "Model documentation support"
        ],
        "limitations": [
            "Benchmark interpretation depends on task design, data quality and contamination controls.",
            "Scores should not be treated as a complete measure of intelligence."
        ],
        "tags": [
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            "Evaluation",
            "Documentation",
            "Contemporary",
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        "timeline": [
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}

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