Summary
In this chapter, we discussed core features of Amazon Comprehend, including the extraction of pre-trained entities such as “Person,” “Date,” and “Location” from text. We then discussed how we can leverage Amazon Comprehend for the document extraction stage of the IDP pipeline. We also discussed how to use Amazon Textract to extract text from a document and pass it to Amazon Comprehend for entity extraction.
We then reviewed the need for custom entities extraction and how to train your own Comprehend custom entity recognizer model. We discussed the two-step process of training a custom entity recognizer and then created an analysis job for custom entities extraction from any type of document.
In the next chapter, we will extend the extraction and enrichment stage of the IDP pipeline using Amazon Comprehend Medical. You will be introduced to the enrichment stage of IDP and discover how to leverage Amazon Comprehend to enrich your...
