From the course: Applied AI: Getting Started with Hugging Face Transformers
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Introduction to named entity recognition
From the course: Applied AI: Getting Started with Hugging Face Transformers
Introduction to named entity recognition
- [Instructor] Named Entity Recognition, or NER for short, is a popular NLP task that has a wide range of applications. NER is used to extract relevant entities from a body of text. These entities may be names, dates, locations, addresses, et cetera. NER models use language semantics to identify the location of the entities and label them. NER helps in automated language understanding systems. For example, in customer support, chatbots and voice bots can use NER to extract specific information that the customer has stated through free text and use this information for further query and response. NER can be used to understand the content of emails and then create automated responses. For example, if the customer is requesting the status of an order number, the order number can be extracted from the email body to query the order status and respond to the email. Similarly, NER can be used to analyze text like reviews and…
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