From the course: Building Apps with Azure AI Language and Python

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Named entity recognition

Named entity recognition

From the course: Building Apps with Azure AI Language and Python

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Named entity recognition

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- [Instructor] Named Entity Recognition or NER runs a predictive model to identify and categorize named entities from an input document. This is also very helpful in scenarios wherein you want to catalog and search your documents. Microsoft Learn enumerates the different types and subtypes of entities that the service can identify and categorize. The link is also shared in the Jupyter Notebook. You again need to install the Azure AI Text Analytics Library if you haven't done so in the previous video. We then load the Azure configurations and create our Text Analytics Client. We then create a helper function that contains our main code. We use this time the recognize_entities method of the client. The method also requires you to fill up the documents parameter. We then iterate through each result and print out the text category, subcategory, confidence score, length, and offset of each entity inside the document. The documents would again be a list of documents containing one or more…

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