删除所有不是名词，动词，形容词，副词或专有名词的单词。 spacy python

Question

我写了下面的代码，我想打印出前10个句子中的单词，我想删除所有不是名词，动词，形容词，副词或专有名称的单词。但是我不知道怎么做？谁能帮我？

! pip install wget
import wget
url = 'https://raw.githubusercontent.com/dirkhovy/NLPclass/master/data/moby_dick.txt'
wget.download(url, 'moby_dick.txt')
documents = [line.strip() for line in open('moby_dick.txt', encoding='utf8').readlines()]

import spacy

nlp = spacy.load('en')

tokens = [[token.text for token in nlp(sentence)] for sentence in documents[:200]]
pos = [[token.pos_ for token in nlp(sentence)] for sentence in documents[:100]]
pos

Answer 1

您需要知道哪些POS符号用于表示这些实体。这是list from Spacy文档。此代码将帮助您满足此要求：

import spacy

nlp = spacy.load('en_core_web_sm') #you can use other methods
# excluded tags
excluded_tags = {"NOUN", "VERB", "ADJ", "ADV", "ADP", "PROPN"}
document = [line.strip() for line in open('moby_dick.txt', encoding='utf8').readlines()]

sentences = document[:10] #first 10 sentences
new_sentences = []
for sentence in sentences:
    new_sentence = []
    for token in nlp(sentence):
        if token.pos_ not in excluded_tags:
            new_sentence.append(token.text)
    new_sentences.append(" ".join(new_sentence))

现在，new_sentences具有与以前相同的句子，但没有任何名词，动词等。您可以通过在sentences和new_sentences上进行迭代以查看不同的内容来确保这一点：

for old_sen, new_sen in zip(sentences, new_sentences):
    print("Before:", old_sen)
    print("After:", new_sen)
    print()
Before: Loomings .
After: .

Before: Call me Ishmael .
After: me .

Before: Some years ago -- never mind how long precisely -- having little or no money in my purse , and nothing particular to interest me on shore , I thought I would sail about a little and see the watery part of the world .
After: Some -- -- or no my , and nothing to me , I I a and the the .

Before: It is a way I have of driving off the spleen and regulating the circulation .
After: It is a I have the and the .

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