There are a number of techniques available to extract relationships. These can be grouped as follows:

Hand-built models are used when we have no training data. This can occur with new business domains or entirely new types of projects. These often require the use of rules. A rule might be:

"If the word "actor" or "actress" is used and not the word "movie" or "commercial", then the text should be classified as a play."

However, this approach takes a lot of effort and needs to be adjusted for the actual text in-hand.

If only a little training data is amiable, then the Naive Bayes classifier is a good choice. When more data is available, then techniques such as SVM, Regularized Logistic Regression, and Random forest can be used.

Although it is useful to understand these techniques in more detail, we will not cover them here as our focus is on the use of these techniques.