Python uses spaCy to implement part of speech tagging

Preparation work: 1. Ensure that the Python interpreter has been installed. 2. Install the spaCy library: Run the command 'pip install - U space'. 3. Download the English model of spaCy: Run the command 'Python - m spacy download en'. Dependent class libraries: -SpaCy: used for Natural language processing tasks, including part of speech tagging, Named-entity recognition, etc. Dataset: SpaCy has pre trained a part of speech annotation model for English text, which we can use for demonstration of part of speech annotation. The source code is as follows: python import spacy #Load English model nlp = spacy.load('en') #Define sample data text = "Apple is looking at buying U.K. startup for $1 billion" #Word segmentation and part of speech tagging doc = nlp(text) for token in doc: print(token.text, token.pos_) Run the above code and the output result is as follows: Apple PROPN is VERB looking VERB at ADP buying VERB U.K. PROPN startup NOUN for ADP $ SYM 1 NUM billion NUM The above code uses the English model from spaCy to annotate the part of speech of the sample data. Each word (token) in 'token. pos'_` The corresponding part of speech is stored in.