Dictionary based Tagging Example

Requirements:

KNIME Textprocessing version 2.9 or later is required to load and execute this workflow.

Description:

The workflow starts with a list of documents. The documents are ten famous fairy tales of the Brothers Grimm. The data is available as drop file in the corresponding drop directories.

Branch 1:

The words of the first dictionary are searched by the Dictionary tagger node in the documents. Found terms in the documents are tagged with PERSON tags. Document terms and dictionary words are compared case insensitive by exact match. Then a bag of words is created and filtered to keep only the tagged terms.

Branch 2:

The words of the second dictionary are search in the documents by the Dictionary tagger. Found terms in the documents are tagged with PERSON tags. Document terms and dictionary words are compared case insensitive by non-exact match, meaning that a document term is tagged if it containes a word of the dictionary. Then a bag of words is created and filtered to keep only the tagged terms.

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