Syntactic Analysis and Patterns NLP Algorithm

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Having a list of tokens, we can start the first stage of in-depth analysis, which is syntactic analysis. In this phase, our algorithm will try to build some recognizable, distinguishable patterns based on the previous list . Depending on the algorithm, these can be completely different groups.

The simplest example would be dividing tokens by ranges that create sentences, for example. Analyzing the text below:

Marcel was supposed to start drawing, but something came up, so he had to postpone it. This situation happened yesterday.
NLP algorithm
Assuming that the given text was correctly parsed into a list of cameroon whatsapp lead tokens in the previous step, during syntactic analysis this list can be parsed into some syntactic groups:

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NLP algorithm example
If the algorithm is unable to distinguish between such groups, analysis may not be possible and the analysis will result in a syntax error.

Semantic Analysis and Transformation NLP Algorithm
Semantic analysis is very dependent on the implementation (natural language processing) and its purpose. During this stage, we need to extract the information we need from the previously organized token structure.

The methodology for finding the intention behind each sentence may be based on predefined algorithms or on certain extended knowledge bases, such as integration with machine learning systems.

An example of extracting information of interest to us from a prepared syntax tree could be diagnosing the emotional value of each sentence in a text.

Assuming that in our database we assign certain emotional coefficients to given words in the range <-1, 1>, where a negative value means a negative relationship
and a positive one means a positive relationship: