Tag nns
You're referring to Named Entity Recognition (NER)!
Named Entity Recognition (NER) is a sub-task of Natural Language Processing (NLP) that involves identifying and categorizing named entities in unstructured text into predefined categories such as:
- Person (e.g., John Smith)
- Organization (e.g., Google)
- Location (e.g., New York City)
- Date (e.g., 2022-07-25)
- Time (e.g., 14:30)
- Event (e.g., World Cup)
- Product (e.g., iPhone)
- Work of Art (e.g., Mona Lisa)
The goal of NER is to automatically identify and classify named entities in text, which can be useful for various applications such as:
- Information retrieval
- Sentiment analysis
- Text summarization
- Question answering
- Entity disambiguation
Some popular NER tools and libraries include:
- spaCy
- Stanford CoreNLP
- NLTK
- GATE
- OpenNLP
Do you have a specific question about NER or would you like to know more about a particular aspect of it?