There’s a blog post on this subject here. The flowchart there gives a good overview of how to approach entity extraction and the following paragraph address extracting names:
The spaCy library offers pretrained entity extractors. As with the word embeddings, only certain languages are supported. If your language is supported, the component ner_spacy is the recommended option to recognise entities like organization names, people’s names, or places. You can try out the recognition in the interactive demo of spaCy.
hi stephens, I have created a bot thats asks user information
(using forms) and stores in database. I want to extract name from the user. so Im using spacy entity extractor and added dimension [‘PERSON’]. I have some doubts in nlu and domain. should I add the entities PERSON for name in nlu and add the entities in domain.
My name is [shanthosh] (PERSON)
I am [Virat] (PERSON)
- type: from_text