PhillyMac/Emotional_Intelligence_Corpus
Emotional Intelligence This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications. 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 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… See the full description on the dataset page: https://huggingface.co/datasets/PhillyMac/Emotional_Intelligence_Corpus.
Emotional Intelligence
This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.
Dataset Description
- Subject: Emotional Intelligence
- Subject Type: topic
- Total Items: 2,294
- Has Embeddings: Yes (all-MiniLM-L6-v2)
- Created: 2026-01-02
Dataset Structure
Each record contains:
text: The content textsource_url: Original source URLsource_title: Title of the source documentsource_domain: Domain of the sourcerelevance_score: Relevance to the subject (0-1)quality_score: Content quality score (0-1)topics: JSON array of detected topicscharacter_count: Length of the textsubject_name: The subject this content relates tosubject_type: "personality" or "topic"extraction_date: When the content was extractedembedding: Pre-computed 384-dimensional embedding vector
Usage
from datasets import load_dataset
dataset = load_dataset("PhillyMac/Emotional_Intelligence_Corpus")
# Access the data
for item in dataset["train"]:
print(item["text"][:100])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.
Generated By
Deku Corpus Builder - An automated corpus building system for AI applications.
