In the previous section, we used some NLP techniques to enhance our knowledge graph. The same techniques can be applied in order to analyze a question written by a user and extract its meaning. Here we are going to use a small Python script to help us convert a user question to a Cypher query.
In terms of NLP, the Python ecosystem contains several packages that can be used. For our needs here, we are going to use spaCy (https://spacy.io/). It is very easy to use, especially if you don't want to bother with technical implementations. It can be easily installed via the Python package manager, pip:
pip install -U spacy
It is also available on conda-forge if you prefer to use conda.
Let's now see how spaCy can help us in building a graph-based search engine. Starting from an English sentence such as Leonardo DiCaprio is born in Los Angeles, spaCy can identify the different parts of the sentence and the relationship between them:
The previous diagram was generated...
