genai-graphrag-python - post review (#434)

* fix cypher statement

* escape asciidoc heading

* typo

Author: martinohanlon

asciidoc/courses/genai-graphrag-python/modules/2-knowledge-graph-pipeline/lessons/5-structured-data/lesson.adoc

@@ -107,8 +107,8 @@ The knowledge graph allows you to summarize the content of each lesson by specif
 ----
 MATCH (lesson:Lesson)<-[:PDF_OF]-(:Document)<-[:FROM_DOCUMENT]-(c:Chunk)
 RETURN lesson.name,
-  [ (c)-[:FROM_CHUNK]->(tech:Technology) | tech.name ] AS technologies,
-  [ (c)-[:FROM_CHUNK]->(concept:Concept) | concept.name ] AS concepts
+  [ (c)<-[:FROM_CHUNK]-(tech:Technology) | tech.name ] AS technologies,
+  [ (c)<-[:FROM_CHUNK]-(concept:Concept) | concept.name ] AS concepts
 ----
 
 Spend some time exploring the knowledge graph and experiment with adding additional data.

asciidoc/courses/genai-graphrag-python/modules/4-customisation/lessons/2-splitting-text/lesson.adoc

@@ -38,7 +38,7 @@ include::{repository-raw}/{branch}/genai-graphrag-python/examples/text_splitter_
 include::{repository-raw}/{branch}/genai-graphrag-python/examples/text_splitter_section.py[tag=splitter]
 ----
 
-The `SectionSplitter` class splits the text based on a section heading (`== `), then creates `TextChunk` objects for each section, and finally returns a `TextChunks` object containing all the chunks.
+The `SectionSplitter` class splits the text based on a section heading (``== ``), then creates `TextChunk` objects for each section, and finally returns a `TextChunks` object containing all the chunks.
 
 You can run the text splitter directly with test data to verify that it is working:
 

asciidoc/courses/genai-integration-langchain/modules/1-langchain/lessons/4-neo4j-graph/lesson.adoc

@@ -64,7 +64,7 @@ You can view the database schema using the Cypher query:
 CALL db.schema.visualization()
 ----
 
-Open the `genai-integration-langchain/scheme_agent.py` file.
+Open the `genai-integration-langchain/schema_agent.py` file.
 
 .schema_agent.py
 [source,python]