Text Processing (POS, Lemma and NER)

Hello all,

I am a new user and I try to Process my text data.
The data and text is in german language.
Currently I have a file with three columns of the type document.
The content of one of these columns I want to tag with a POS-Tagger.
I tried the Dictionary Tagger with an special model, download from the internet with a lot of pre-defined tagged words.
But the result of the node is the same of the source.
Furthermore I tried with the Bag Of Words Node to seperate all word in one special row, but with the same effect.

That is just one of my problems, but I think the biggest one.
Afterwards I want to use the Lemma of all adjectives and verbs and I want to recognize all named entities by a NER Node.

Is here anyone, who could help me?

Thank you.


Thank you for your question. Have you looked at the examples on the Examples Server and the KNIME Community Workflow Hub under 08_Other_Analytics_Types/01_Text_Processing? Here you find, for example, a workflow that tags documents with a POS-Tagger and visualizes the results in a tag cloud. The workflow is called 05_Named_Entity_Tag_Cloud. Another workflow that you find there and that could be of interest for you is 14_NER_Tagger_Model_Training. This workflow generates and evaluates an NER model.

Hope that helps,

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