zarnite/reolyy-edit-intent-to-timeline

--- 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 - video-editing - timeline - creative-tools - gold-track - benchmark-starter pretty_name: Reolyy Edit Intent to Timeline 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 --- # Reolyy Edit Intent to Timeline ## Dataset Description Creator intent plus clip metadata and transcript slices mapped to structured timeline edits. ## 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 Timeline planning is central to creator tooling, and high-context editing benchmarks help separate generic language ability from actual packaging skill. ## Benchmark Goal Evaluate timeline construction, proof preservation, packaging completeness, and editing decisions under realistic creative constraints. ## 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: 20,000 - Validation: 2,000 - Test: 2,000 - Total target rows: 24,000 ## Recommended Metrics - `timeline_segment_iou` - `packaging_completeness` - `constraint_fidelity` - `proof_preservation` - `caption_readability` ## 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 - `creative_brief`: audience, goals, must-keep proof, and things to avoid. - `footage_inventory`: structured clip metadata plus transcript snippets. - `reference_packaging`: hook, titles, caption plan, audio plan, and grade plan. - `reference_qc_checklist`: production-ready checks for the finished cut. - `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/reolyy-edit-intent-to-timeline` - Example upload command: `python upload_to_huggingface.py --dataset-folder "push/high-ecosystem-need/Reolyy-Edit-Intent-to-Timeline" --repo-id "zarnite/reolyy-edit-intent-to-timeline"` - 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/Reolyy-Edit-Intent-to-Timeline" --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： - 原创 任务类别： - 文本生成 标签： - Zarnite - 基准测试（benchmark） - 视频编辑 - 时间线 - 创意工具 - 金标准赛道（gold-track） - 基准测试入门包（benchmark-starter） 展示名称：Reolyy 编辑意图转时间线 规模类别： - 10K<n<100K 配置项： - 配置名称：default 数据文件： - 拆分集：训练集（train），路径：data/train.jsonl - 拆分集：验证集（validation），路径：data/validation.jsonl - 拆分集：测试集（test），路径：data/test.jsonl --- # Reolyy 编辑意图转时间线 ## 数据集概述 将创作者意图、剪辑元数据与转录片段映射为结构化时间线编辑方案的数据集。 ## 团队归属说明 本数据集由Zarnite团队通过内部基准测试设计、生成与质量控制流程创建并审核，应作为Zarnite出品的基准测试入门包进行发布，而非单纯的人工采集的领域语料库。 ## 生态需求等级 高生态需求等级 ## 该类别的吸引力所在 时间线规划是创作者工具的核心功能，高上下文编辑类基准测试能够有效区分通用语言能力与实际内容包装技能。 ## 基准测试目标 评估模型在真实创意约束下的时间线构建、素材留存、内容包装完整性与编辑决策能力。 ## 本文件夹包含内容 - `data/train.jsonl`、`data/validation.jsonl`与`data/test.jsonl`：基准测试入门拆分集，总计1200条数据。 - `schema.json`：用于数据行校验的JSON Schema文件。 - `benchmark_spec.json`：包含评估指标、质量门槛与目标发布规模的配置文件。 - `LICENSE.md`：本文件夹独立发布所需的本地许可证声明。 - `PUBLISHING.md`：针对Hugging Face仓库的专属发布指南。 - `hf_repo_template.json`：上传脚本使用的机器可读仓库模板文件。 ## 公开发布目标规模 - 训练集：20000条 - 验证集：2000条 - 测试集：2000条 - 总目标数据行数：24000条 ## 推荐评估指标 - `timeline_segment_iou`（时间线分段交并比） - `packaging_completeness`（包装完整性） - `constraint_fidelity`（约束保真度） - `proof_preservation`（素材留存率） - `caption_readability`（字幕可读性） ## 金标准赛道基准测试资源 - `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`：通过双审与仲裁机制审核验证集与测试集数据行的操作规范。 - `BASELINE_EVAL_SPEC.json`：包含预期输出契约、分块报告与发布阈值的基准评估规范文件。 - `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评分配置文件。 - `prediction_template.jsonl`：基准测试提交或基准运行的入门模板文件。 ## 扩展数据行结构说明 - `creative_brief`（创意简报）：目标受众、创作目标、必须留存的素材与需规避的内容。 - `footage_inventory`（素材清单）：结构化的剪辑元数据与转录片段。 - `reference_packaging`（参考包装方案）：开场钩子、标题、字幕规划、音频规划与调色规划。 - `reference_qc_checklist`（参考质量检查清单）：成品剪辑的量产级检查项。 - `difficulty_rationale`（难度合理性说明）：解释该数据行为何归属当前难度层级而非更低难度分块。 - `benchmark_slices`（基准测试分块）：已命名的报告分块，如审批摩擦、素材留存或引用陷阱。 - `adversarial_features`（对抗特征）、`expected_failure_modes`（预期失效模式）与`review_readiness`（审核就绪度）：说明该数据行的测试目标与金标准赛道审核人员的处理方式。 - `evidence_manifest`（证据清单）、`reference_variants`（参考变体）与`negative_examples`（负样本）：分别对应源证据边界、可接受的替代答案与具体失效案例。 ## Hugging Face部署说明 本文件夹为独立完整的包，可以直接作为独立的Hugging Face数据集仓库上传。 - 推荐仓库ID：`zarnite/reolyy-edit-intent-to-timeline` - 示例上传命令：`python upload_to_huggingface.py --dataset-folder "push/high-ecosystem-need/Reolyy-Edit-Intent-to-Timeline" --repo-id "zarnite/reolyy-edit-intent-to-timeline"` - 可通过向上传脚本传入`--namespace YOUR_USERNAME`参数替换命名空间。 ## 本地评估说明 - 示例评估命令：`python run_priority_eval.py --dataset-folder "push/high-ecosystem-need/Reolyy-Edit-Intent-to-Timeline" --splits validation test` - `prediction_template.jsonl`提供了本地提交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包装的原创入门示例。