spaCy是最好的文本分析库之一。spaCy在大型信息提取任务方面表现出色,并且是世界上最快的之一。这也是准备用于深度学习的文本的最佳方法。spaCy比NLTKTagger和TextBlob更快,更准确。
pip install spacy python -m spacy download en_core_web_sm
#importing loading the library import spacy # python -m spacy download en_core_web_sm nlp = spacy.load("en_core_web_sm") #POS-TAGGING # Process whole documents text = ("""My name is Vishesh. I love to work on data science problems. Please check out my github profile!""") doc = nlp(text) # Token and Tag for token in doc: print(token, token.pos_) # You want list of Verb tokens print("Verbs:", [token.text for token in doc if token.pos_ == "VERB"]) #Lemmatization : It is a process of grouping together the inflected #forms of a word so they can be analyzed as a single item, #identified by the word’s lemma, or dictionary form. import spacy # Load English tokenizer, tagger, # parser, NER and word vectors nlp = spacy.load("en_core_web_sm") # Process whole documents text = ("""My name is Vishesh. I love to work on data science problems. Please check out my github profile!""") doc = nlp(text) for token in doc: print(token, token.lemma_)