zarnite/zarn-creative-brief-to-asset-plan

--- language: - en license: apache-2.0 annotations_creators: - expert-generated - machine-generated language_creators: - expert-generated - machine-generated source_datasets: - original task_categories: - text-generation tags: - zarnite - benchmark - creative-briefs - project-planning - creative-tools - gold-track - benchmark-starter pretty_name: Zarn Creative Brief to Asset Plan size_categories: - 10K<n<100K configs: - config_name: default data_files: - split: train path: data/train.jsonl - split: validation path: data/validation.jsonl - split: test path: data/test.jsonl --- # Zarn Creative Brief to Asset Plan ## Dataset Description Creative briefs mapped to delivery plans, asset priorities, review checkpoints, and dependencies. ## Team Attribution This dataset was created and reviewed by the Zarnite team through internal benchmark design, generation, and quality-control workflows. It should be presented as a Zarnite-authored benchmark starter pack, not as a purely human-collected field corpus. ## Ecosystem Need Tier High Ecosystem Need ## Why This Category Is Attractive Turning messy business goals into an actionable creative system is a high-value creative-ops use case, but few public datasets capture asset hierarchy, review flow, and handoff logic together. ## Benchmark Goal Evaluate whether a model can transform a creative brief into a production-ready asset plan with strong message hierarchy, approval flow, and downstream handoff clarity. ## Included In This Folder - `data/train.jsonl`, `data/validation.jsonl`, `data/test.jsonl`: starter benchmark splits with 1200 total rows. - `schema.json`: JSON Schema for row validation. - `benchmark_spec.json`: metrics, quality gates, and target release scale. - `LICENSE.md`: folder-local license notice for self-contained publishing. - `PUBLISHING.md`: repo-specific publish instructions for Hugging Face. - `hf_repo_template.json`: machine-readable repo template used by the uploader script. ## Target Public Scale - Train: 16,000 - Validation: 2,000 - Test: 2,000 - Total target rows: 20,000 ## Recommended Metrics - `coverage_and_constraint_score` - `deliverable_fit` - `message_hierarchy_quality` - `dependency_clarity` - `handoff_readiness` ## Gold-Track Benchmark Assets - `ANNOTATION_GUIDELINES.md`: how to expand rows without drifting from the benchmark purpose. - `REVIEW_PROTOCOL.md`: how to audit validation and test rows with dual review and adjudication. - `BASELINE_EVAL_SPEC.json`: expected output contract, slice reporting, and release thresholds. - `RELEASE_CHECKLIST.md`: final pre-publish checks for the public Hugging Face release. - `SCORING_PROFILE.json`: prediction keys, scoring expectations, and slice reporting requirements. - `prediction_template.jsonl`: starter template for benchmark submissions or baseline runs. ## Expanded Row Anatomy - `project_frame`: why the work matters now, what commercial goal it serves, and what tension the plan must resolve. - `message_hierarchy`: the ordered narrative the asset family should preserve. - `channel_strategy` and `approval_matrix`: how the plan changes by surface and who has to approve what. - `reference_brief_package`: the gold high-level asset system, not just a loose brainstorm. - `difficulty_rationale`: why the row belongs in its difficulty bucket instead of a weaker slice. - `benchmark_slices`: named reporting slices such as approval friction, proof preservation, or citation traps. - `adversarial_features`, `expected_failure_modes`, and `review_readiness`: what the row is testing and how a gold-track reviewer should treat it. - `evidence_manifest`, `reference_variants`, and `negative_examples`: the source evidence boundary, acceptable alternate answers, and concrete failure cases. ## Hugging Face Deployment This folder is self-contained and can be uploaded as its own Hugging Face dataset repository. - Suggested repo id: `zarnite/zarn-creative-brief-to-asset-plan` - Example upload command: `python upload_to_huggingface.py --dataset-folder "push/high-ecosystem-need/Zarn-Creative-Brief-to-Asset-Plan" --repo-id "zarnite/zarn-creative-brief-to-asset-plan"` - You can swap the namespace by passing `--namespace YOUR_USERNAME` to the uploader. ## Local Evaluation - Example eval command: `python run_priority_eval.py --dataset-folder "push/high-ecosystem-need/Zarn-Creative-Brief-to-Asset-Plan" --splits validation test` - `prediction_template.jsonl` gives the required output shape for local or leaderboard-style submissions. ## License This package is marked `apache-2.0`. The rows in this folder are original starter examples for benchmark packaging.语言: - 英语 许可证: apache-2.0 注释生成者: - 专家生成 - 机器生成 语言生成者: - 专家生成 - 机器生成 源数据集: - 原始数据集 任务类别: - 文本生成 标签: - zarnite - 基准测试 - 创意简报 - 项目规划 - 创意工具 - 金牌赛道 - 基准测试入门套件 展示名称: Zarn 创意简报转创意资产计划 规模分类: - 10K<n<100K 配置项: - 配置名称: default 数据文件: - 拆分集: train 路径: data/train.jsonl - 拆分集: validation 路径: data/validation.jsonl - 拆分集: test 路径: data/test.jsonl # Zarn 创意简报转创意资产计划 ## 数据集描述 将创意简报（creative brief）映射至交付计划、资产优先级、评审检查点与依赖关系的数据集。 ## 团队归属声明 本数据集由Zarnite团队通过内部基准测试设计、生成与质量管控流程创建并审核。本数据集应作为Zarnite出品的基准测试入门套件（benchmark starter pack）进行展示，而非纯人工收集的实地语料库。 ## 生态系统需求层级 高生态系统需求 ## 该类别的吸引力所在 将杂乱的业务目标转化为可落地的创意系统是高价值的创意运营（creative-ops）场景，但目前鲜有公开数据集能够同时涵盖资产层级、评审流程与交接逻辑。 ## 基准测试目标 评估模型能否将创意简报转化为具备清晰信息层级、审批流程与下游交接清晰度的可投产创意资产计划。 ## 本文件夹包含内容 - `data/train.jsonl`、`data/validation.jsonl`、`data/test.jsonl`：入门基准测试拆分集，总计1200条数据。 - `schema.json`：用于数据行校验的JSON Schema。 - `benchmark_spec.json`：包含评估指标、质量门槛与目标发布规模的文件。 - `LICENSE.md`：用于独立发布的文件夹本地许可证声明。 - `PUBLISHING.md`：面向Hugging Face的特定仓库发布指南。 - `hf_repo_template.json`：上传脚本使用的机器可读仓库模板。 ## 目标公开规模 - 训练集：16000条 - 验证集：2000条 - 测试集：2000条 - 目标总数据行：20000条 ## 推荐评估指标 - 覆盖度与约束得分（coverage_and_constraint_score） - 交付物适配度（deliverable_fit） - 信息层级质量（message_hierarchy_quality） - 依赖清晰度（dependency_clarity） - 交接就绪度（handoff_readiness） ## 金牌赛道基准测试资源 - `ANNOTATION_GUIDELINES.md`：如何在不偏离基准测试目标的前提下扩展数据行的指南。 - `REVIEW_PROTOCOL.md`：如何通过双评审与裁决机制审核验证集与测试集数据行的流程。 - `BASELINE_EVAL_SPEC.json`：包含预期输出契约、分块报告与发布阈值的文件。 - `RELEASE_CHECKLIST.md`：面向Hugging Face公开发布的最终预发布检查清单。 - `SCORING_PROFILE.json`：包含预测键、评分预期与分块报告要求的文件。 - `prediction_template.jsonl`：用于基准测试提交或基线运行的入门模板。 ## 扩展数据行结构解析 - `project_frame`：项目框架：说明当前工作的重要性、服务的商业目标以及计划需解决的核心矛盾。 - `message_hierarchy`：信息层级：创意资产家族需遵循的有序叙事逻辑。 - `channel_strategy`与`approval_matrix`：渠道策略与审批矩阵：说明计划如何因平台而异，以及各审批节点的权责划分。 - `reference_brief_package`：参考简报包：高标准的顶层创意资产系统，而非零散的头脑风暴内容。 - `difficulty_rationale`：难度说明：解释该数据行为何归属于当前难度层级而非更简单的分组。 - `benchmark_slices`：基准测试分块：命名化的报告分块，如审批摩擦、证据保留或引用陷阱。 - `adversarial_features`、`expected_failure_modes`与`review_readiness`：对抗特征、预期失效模式与评审就绪度：说明该数据行的测试目标，以及金牌赛道评审人员的处理方式。 - `evidence_manifest`、`reference_variants`与`negative_examples`：证据清单、参考变体与负样本：说明源证据边界、可接受的替代答案与具体失效案例。 ## Hugging Face部署 本文件夹为独立完整的包，可直接上传为独立的Hugging Face数据集仓库。 - 推荐仓库ID：`zarnite/zarn-creative-brief-to-asset-plan` - 示例上传命令：`python upload_to_huggingface.py --dataset-folder "push/high-ecosystem-need/Zarn-Creative-Brief-to-Asset-Plan" --repo-id "zarnite/zarn-creative-brief-to-asset-plan"` - 可通过向上传脚本传递`--namespace YOUR_USERNAME`参数替换命名空间。 ## 本地评估 - 示例评估命令：`python run_priority_eval.py --dataset-folder "push/high-ecosystem-need/Zarn-Creative-Brief-to-Asset-Plan" --splits validation test` - `prediction_template.jsonl`提供了本地或排行榜式提交所需的输出格式。 ## 许可证 本套件采用Apache-2.0许可证。本文件夹内的数据行均为基准测试打包的原始入门示例。