These are the text analyzers that are bundled with the NLP-ENGINE.
This is an example analyzer that tries to highlight the power of NLP++ and the knowledge base. It is not meant to be thorough but simply illustrate the capabilities of NLP++.
NOTE: the "words" stubs in the analyzer sequence are from the first version of VisualText which auto-generated rules from examples. Currently, this feature is not available in the VSCode version of VisualText.
This is an example of an analyzer that works over a directory of files with a persistent knowledge base. In this case, the knowledge is simply a counter. But this can serve as a basis for much more complex tasks where as texts are processed, knowledge can be used that persists between the processing of each file.
These are the NLP++ tutorial analyzers that accompany the NLP++ tutorial videos on the NLP VisualText YouTube Channel.
This analyzer was developed over 20 years for English and is a purely syntactic analyzer for English. It will come up with a syntactic parse tree for any English text.
The dictionary came from an early version of wordnet.