For more technologies supported by Talend, see Talend components.
This Job uses tNLPPreprocessing to divide the input text into tokens. Then, the tokens are converted to the CoNLL format using tNormalize. You will be able to use this CoNLL file to learn a classification model for extracting named entities in text data.
Preparing a text sample by dividing it into tokens. The tokens will be used for training a classification model.
Learning a classification model, designing the features and evaluating the model.
For an example of how to generate a classification model using tNLPModel, see Generating a classification model.
Applying the model on the full text to extract named entities using tNLPPredict.
For an example of how to extract named entities using a classification model, Extracting named entities using a classification model.
For further information about natural language processing, see Natural Language Processing using Talend Studio.