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For a better understanding of what Saga is and what the purpose of the UI is, please check out this presentation in Teams.:
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In this screen you will find your tags as facets. So when selected you'll see search results containing your tags. In the following image we are clearing facets then selecting only {fire-by-bird} to check the comments that talk about engines getting on fire due to birds.
e. After reviewing results you can continue iterating on this process of reviewing results and tweaking your tags and pipelines to create the best model to use for you specific use case.
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In order to use it as recognizer, you only need to add the recognizer to your tag, then choose a model, the probability threshold used to decide if something is a match or not and finally normalization tags in case you want to cleanse and normalize the input to machine learning.
Let's use the {human} tag to test this functionality:
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e. Choose one of the models that come by default: "en-ner-person.bin". This model was trained to identify English names of people.
f. Put Enter this text in the preview in order to check out the Saga graph: "Several employees work from home, Joseph is one of them, Paul too". As you can see in the following image, the recognizer tags 'Joseph' and 'Paul' as humans{human}:
3.2.1.2 Using it as a trainer
In order to train a model we need to use another recognizer as the base and a dataset that contains people's names. We'll use the Entity recognizer that we set as disabled and the Android Reddit dataset.
a. Enable the Entity recognizer for the {human} tag
b. In the Name recognizer:
- set the Name recognizer to disabled
- set the 'Model' field to --NONE–
- add 'human' value to the field 'Normalized Tags'
- click on the 'Train' button.
c. Once the Train dialog opens, select the AndroidReddit dataset and set the machine learning options according to your needs. In this case we are leaving everything with default values.
d. Check out the Background Processes tab to see the progress of the training
e. Once the process completes:
- disable the Entity recognizer for the {human} tag again
- enable the Name recognizer
- in the Name recognizer, select your recently created model (result from the training). It should be something like "human-[date stamp here]", for example: human-20190206172621. You can also use the option --LATEST-- so it will always
use the most recent model you have created.
- use the preview functionality to test your newly created model. Enter the same text as before in the preview text box: "Several employees work from home, Joseph is one of them, Paul too"
- check if names are tagged as well
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