PhillyMac/Coaching_and_Developing_Others_2

---
license: cc0-1.0
task_categories:
- text-generation
- feature-extraction
language:
- en
tags:
- corpus
- leadership
- historical
- deku-corpus-builder
size_categories:
- 1K<n<10K
---

# Coaching and Developing Others 2

This corpus was automatically generated by the **Deku Corpus Builder** for use in RAG-based AI applications.

## Dataset Description

- **Subject**: Leader as Coach Developing Others
- **Subject Type**: topic
- **Total Items**: 2,789
- **Items Requiring Attribution**: 0
- **Has Embeddings**: Yes (all-MiniLM-L6-v2)
- **Created**: 2026-03-27

## Dataset Structure

Each record contains:
- `text`: The content text
- `source_url`: Original source URL
- `source_title`: Title of the source document
- `source_domain`: Domain of the source
- `license_type`: License classification (e.g. `public_domain`, `cc_by`, `cc_by_sa`)
- `attribution_required`: Boolean — True for CC BY / CC BY-SA and other attribution-required licenses
- `attribution_text`: Formatted Creative Commons attribution string (empty if not required)
- `license_url`: URL to the CC license deed (empty if not required)
- `relevance_score`: Relevance to the subject (0-1)
- `quality_score`: Content quality score (0-1)
- `topics`: JSON array of detected topics
- `character_count`: Length of the text
- `subject_name`: The subject this content relates to
- `subject_type`: "personality" or "topic"
- `extraction_date`: When the content was extracted
- `embedding`: Pre-computed 384-dimensional embedding vector

## Attribution

0 of 2,789 chunks in this corpus require attribution under their source license.
When building lessons from these chunks, the `attribution_text` field must be surfaced
in the lesson output per the Legend Leadership Attribution Tracking Spec.

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("PhillyMac/Coaching_and_Developing_Others_2")

# Access attribution-required chunks
for item in dataset["train"]:
if item["attribution_required"]:
print(item["attribution_text"])
```

## Integration with RAG

This dataset is designed to be integrated with existing embedded corpuses. The embeddings use the `sentence-transformers/all-MiniLM-L6-v2` model, compatible with FAISS indexing.

## License

Content is sourced from public domain and Creative Commons licensed materials.
See individual `license_type` fields for per-chunk licensing details.

## Generated By

[Deku Corpus Builder](https://github.com/PhillyMac/deku-corpus-builder) - An automated corpus building system for AI applications.

---
许可证: CC0 1.0协议
任务类别:
- 文本生成
- 特征提取
语言:
- 英语
标签:
- 语料库
- 领导力
- 历史
- deku语料库构建器（deku-corpus-builder）
样本规模:
- 1000 < n < 10000
---

# 《指导与培养他人2》

本语料库由**Deku语料库构建器（Deku Corpus Builder）**自动生成，专为基于检索增强生成（Retrieval-Augmented Generation，RAG）的人工智能应用打造。

## 数据集概览

- **主题**: 以教练角色培养下属的领导者
- **主题类型**: 话题主题
- **总条目数**: 2789条
- **需标注来源的条目数**: 0条
- **已生成词嵌入**: 是（采用all-MiniLM-L6-v2模型）
- **创建时间**: 2026年3月27日

## 数据集结构

每条记录包含以下字段：
- `text`: 文本内容
- `source_url`: 原始来源链接
- `source_title`: 来源文档标题
- `source_domain`: 来源域名
- `license_type`: 许可证分类（例如`public_domain`, `cc_by`, `cc_by_sa`）
- `attribution_required`: 布尔值——若采用CC BY/CC BY-SA或其他需标注来源的许可证，则取值为真
- `attribution_text`: 格式化的知识共享署名字符串（无需标注时为空）
- `license_url`: 知识共享许可证deed链接（无需标注时为空）
- `relevance_score`: 与主题的相关度评分（取值范围0至1）
- `quality_score`: 内容质量评分（取值范围0至1）
- `topics`: 检测到的主题的JSON数组
- `character_count`: 文本字符数
- `subject_name`: 该内容关联的主题名称
- `subject_type`: 取值为"personality"或"topic"
- `extraction_date`: 内容提取时间
- `embedding`: 预计算的384维词嵌入向量

## 署名说明

本语料库的2789个文本块中，无一条需要依据其来源许可证标注来源。在基于这些文本块构建课程时，需按照《Legend Leadership Attribution Tracking Spec》规范，在课程输出中展示`attribution_text`字段内容。

## 使用方法

python
from datasets import load_dataset

dataset = load_dataset("PhillyMac/Coaching_and_Developing_Others_2")

# Access attribution-required chunks
for item in dataset["train"]:
if item["attribution_required"]:
print(item["attribution_text"])

## 与检索增强生成（RAG）系统集成

本数据集可与现有嵌入语料库集成。其词嵌入采用`sentence-transformers/all-MiniLM-L6-v2`模型，兼容FAISS索引构建。

## 许可证说明

本数据集内容来源于公有领域及知识共享许可协议授权的素材。各文本块的具体许可信息请参阅各自的`license_type`字段。

## 生成方

[Deku语料库构建器（Deku Corpus Builder）](https://github.com/PhillyMac/deku-corpus-builder)——一款面向人工智能应用的自动化语料库构建系统。