Earlier this year, Amazon Comprehend, a natural language processing (NLP) service that uses machine learning (ML) to discover insights from text, launched the Targeted Sentiment feature. With Targeted Sentiment, you can identify groups of mentions (co-reference groups) corresponding to a single real-world entity or attribute, provide the sentiment associated with each entity mention, and offer the classification of the real-world entity based on a pre-determined list of entities.
Today, we’re excited to announce the new synchronous API for targeted sentiment in Amazon Comprehend, which provides a granular understanding of the sentiments associated with specific entities in input documents.
In this post, we provide an overview of how you can get started with the Amazon Comprehend Targeted Sentiment synchronous API, walk through the output structure, and discuss three separate use cases.
Targeted sentiment use cases
Real-time targeted sentiment analysis in Amazon Comprehend has several applications to enable accurate and scalable brand

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