# tNLPModel

Uses an input in CoNLL format and automatically generates token-level features to create a model for classification tasks like Named Entity Recognition (NER).

This component can run only with Spark 1.6.

For more technologies supported by Talend, see [Talend components](https://help.qlik.com/talend/r/en-US/7.3/components/natural-language-processing).

### In this section

* [tNLPModel properties for Apache Spark Batch](https://help.qlik.com/talend/en-US/components/7.3/natural-language-processing/tnlpmodel-properties-for-apache-spark-batch)

**Related concepts**

[Preparing a text sample to be used for learning a model](https://help.qlik.com/talend/en-US/components/7.3/natural-language-processing/tnlppreprocessing-tnlpmodel-ts3configuration-preparing-text-sample-to-be-used-for-learning-model-this-job)

[Extracting named entities using a classification model](https://help.qlik.com/talend/en-US/components/7.3/natural-language-processing/tnlppredict-tnlpmodel-thdfsconfiguration-ts3configuration-extracting-named-entities-using-classification-model-the)

[Generating a classification model](https://help.qlik.com/talend/en-US/components/7.3/natural-language-processing/tnlpmodel-tnlppredict-thdfsconfiguration-ts3configuration-generating-classification-model-this-job)