POS Tagger

This node assigns to each term of a document a part of speech (POS) tag. Therefore the Penn Treebank tag set is used, for details click here. The underlying tagger model deciding what tag to assign to which term is a model of the OpenNLP framework version 1.8.4 (details).

Options

General options

Document column
The column containing the documents to tag.
Replace column
If checked, the documents of the selected document column will be replaced by the new tagged documents. Otherwise the tagged documents will be appended as new column.
Append column
The name of the new appended column, containing the tagged documents.
Word tokenizer
Select the tokenizer used for word tokenization. Go to Preferences -> KNIME -> Textprocessing to read the description for each tokenizer.
Number of maximal parallel tagging processes
Defines the maximal number of parallel threads that are used for tagging. Please note, that for each thread a tagging model will be loaded into memory. If this value is set to a number greater than 1, make sure that enough heap space is available, in order to be able to load the models. If you are not sure how much heap is available for KNIME, leave the number to 1.

Input Ports

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The input table containing the documents to tag.

Output Ports

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An output table containing the tagged documents.

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Workflows

Links

Developers

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Installation

To use this node in KNIME, install the extension KNIME Textprocessing from the below update site following our NodePit Product and Node Installation Guide:

v5.4

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland
Plugin version: 5.4.0.v202409110759
On NodePit since: 2024-12-06
Last update: 2024-12-17
Tags: Streamable
KNIME versions: Since v3.6

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