Is there an error in this graph embedding tutorial?

[lingvisa]

I am looking at this graph embedding tutorial, as shown below:

Neo4j Graph Database Platform

Tutorial: Applied Graph Embeddings - Developer Guides

This guide provides a hands on walk through of the node2Vec graph embedding algorithm in the Neo4j Data Science Library.

https://neo4j.com/developer/graph-data-science/applied-graph-embeddings/

In the graph creation cypher script, there is only one node type, Place:

CREATE CONSTRAINT ON (p:Place) ASSERT p.name IS UNIQUE;

:auto USING PERIODIC COMMIT 1000
LOAD CSV WITH HEADERS FROM "https://github.com/neo4j-examples/graph-embeddings/raw/main/data/roads.csv"
AS row

MERGE (origin:Place {name: row.origin_reference_place})
SET origin.countryCode = row.origin_country_code

MERGE (destination:Place {name: row.destination_reference_place})
SET destination.countryCode = row.destination_country_code

MERGE (origin)-[eroad:EROAD {number: row.road_number}]->(destination)
SET eroad.distance = toInteger(row.distance), eroad.watercrossing = row.watercrossing;

It created only one node type, Place without Country, but in the tutorial text, and the schema visualization, it shows there are two node types, Place & Country and a relationship, place_in_country, as shown below:

How could it be possible based on the cypher script? I created the graph using the script and get the schema visualization as below, which is consistent with the script:

So is the schema diagram in the tutorial not quite right? Just curious about this.

[lingvisa · Accepted solution]

OK. I got this updated cypher script which is consistent with the tutorial text:

github.com

neo4j-examples/graph-embeddings/blob/main/notebooks/00_Import.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing the European Roads dataset\n",
    "\n",
    "In this notebook we're going to import the European Roads dataset into Neo4j. Let's first import the Neo4j Python driver:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [

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