The Intent stage does a semantic comparison of a provided sentence against possible intents the recognizer already has. If the confidence value is in the threshold, it will create a tag holding the intent.
This recognizer can be used with 2 model types: - A frozen Universal Sentence Encoder TensorFlow model. This one is stored in "[saga-home]\tf-models" directory.
- Any of the models that create embeddings that are available in the Python Bridge.
Both the intents stored in the recognizer as the query entered by the user are encoded (using sentence embedding vectors) and then compared. The intent recognizer will chose the intent that best matches the query. |