Use a Python script that employs spaCy to help automate the training of your Oracle Digital Assistant chatbot.
Creating intents and entities is one of the few time-consuming tasks that Oracle Digital Assistant developers may need to accomplish when defining a new skill (chatbot). Of course, rather than creating intent and entity definitions one at a time in the Bot Builder, you can import CSV files containing the intent and entity definitions, respectively.
However, if you are creating a skill from scratch, you most likely don’t have those definitions in advance, even if you have a large volume of utterances—what the users say—gathered from real requests submitted by your customers. You still need to sort the utterances, based on the intent—user intention—behind them. And to create entity definitions, you’ll need to identify entities and look for synonyms for each entity—because an entity modifies an intent.
This is where using natural-language processing (NLP) tools such as spaCy comes in very handy, enabling you to perform these tasks programmatically and, as a result, automating the process of generating entity and intent definitions. Read the complete article here.
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