File size: 2,527 Bytes
1a82530 ffd5419 80ab022 ffd5419 80ab022 ffd5419 80ab022 ffd5419 80ab022 1a82530 ffd5419 80ab022 ffd5419 80ab022 ffd5419 80ab022 ffd5419 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | ---
license: cc0-1.0
task_categories:
- text-generation
- feature-extraction
language:
- en
tags:
- corpus
- leadership
- historical
- deku-corpus-builder
size_categories:
- 1K<n<10K
---
# Decision Making Content 2
This corpus was automatically generated by the **Deku Corpus Builder** for use in RAG-based AI applications.
## Dataset Description
- **Subject**: Decision Making
- **Subject Type**: topic
- **Total Items**: 98
- **Items Requiring Attribution**: 0
- **Has Embeddings**: Yes (all-MiniLM-L6-v2)
- **Created**: 2026-03-21
## 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 98 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/Decision_Making_Content_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.
|