Textblob word segmentation practice

Environmental construction and preparation work: 1. Ensure that the Python environment is installed (recommended Python version 3. x) 2. Install the TextBlob library and nltk module Install the TextBlob library and nltk module: Install the TextBlob library using the following command: pip install textblob Install the nltk module using the following command: pip install nltk Dependent class libraries: -When building the environment, the dependent TextBlob and nltk class libraries were already installed. Dataset introduction and download website: The TextBlob library comes with some corpora, such as the English dataset in Corpora, which can be directly accessed and used through the API of the TextBlob library. If you need datasets in other languages, you need to download them yourself. Sample data and complete implementation examples: We will segment an English sentence and calculate the part of speech of each word. The sample code is as follows: python from textblob import TextBlob #Enter an English sentence sentence = "I love natural language processing" #Create a TextBlob object blob = TextBlob(sentence) #Participle words = blob.words #Obtain the part of speech label for each word tags = blob.tags #Print segmentation results and corresponding part of speech labels Print ("segmentation result:", words) Print ("Part of speech tags:", tags) Output results: Word segmentation result: ['I ',' love ',' natural ',' language ',' processing '] Part of speech labels: [('I ','PRP'), ('love ','VBP'), ('natural ','JJ'), ('language ','NN'), ('processing ','NN')] The above code uses the TextBlob library to segment English sentences, and uses the built-in part of speech tagging function of the library to output segmentation results and corresponding part of speech tags.