August 15, 2023

Scenario: Preparing a text sample to be used for learning a model – Docs for ESB 6.x

Scenario: Preparing a text sample to be used for learning a model

This scenario applies only to a subscription-based Talend Platform solution with Big data or Talend Data Fabric.

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.

Extracting names entities from text data is a three-phase operation:

  1. Preparing a text sample by dividing it into tokens. The tokens will be used
    for training a classification model.

  2. Learning a classification model, designing the features and evaluating the
    model.

    You can find an example of how to generate a named
    entity recognition model on Talend Help Center (https://help.talend.com).

  3. Applying the model on the full text to extract named entities using
    tNLPPredict.

    You can find an example of how to extract named
    entities using a classification model on Talend Help Center (https://help.talend.com).

You can find more information about natural language processing on
Talend Help Center (https://help.talend.com).


Document get from Talend https://help.talend.com
Thank you for watching.
Subscribe
Notify of
guest
0 Comments
Inline Feedbacks
View all comments
0
Would love your thoughts, please comment.x
()
x