Entity Communication Networks
Extract structured communication metadata from documents and build entity networks in Neo4j
In this 2-hour course, you will learn
Welcome to the Entity Communication Networks course.
In this hands-on course, you will extract text from raw documents, parse it into structured records, and build a communication network in Neo4j. You'll handle OCR noise, build rule-based and LLM-based parsers, train an NER model, and combine them into a hybrid pipeline that imports a metadata graph of entities and their communications.
By the end, you'll also receive a prompt pack — an LLM project that examines your own data, references the techniques from this course, and builds a custom pipeline for any document source. The course teaches you the concepts; the pack applies them to your data.
Before taking this course, you should have:
- Completed the Cypher Fundamentals course, or equivalent Cypher experience
- Basic understanding of Neo4j property graph concepts
- Familiarity with Python
PDF extraction
Document parsing
LLM parsing
Hybrid pipelines
Neo4j import
2 modules, 2 hours.
- What's in your documents?5 min
- Types of Graph5 min
- Parsing Approaches5 min
- Layout-aware extraction5 min
- Parsing libraries5 min
- Rule-based parsing5 min
- Building templates5 min
- ML-based parsing5 min
- Parsing with an LLM5 min
- The hybrid pipeline5 min
- Normalize your data5 min
- Import to Neo4j5 min
- Investigate your graph5 min
- Prompt pack5 min