TextBlob和NLTK词性标注准确率

Question

到目前为止，我有下面的代码

from textblob import TextBlob
class BrinBot:

    def __init__(self, message): #Accepts the message from the user as the argument
        parse(message)

class parse:
    def __init__(self, message):
        self.message = message
        blob = TextBlob(self.message)
        print(blob.tags)

BrinBot("Handsome Bob's dog is a beautiful Chihuahua")

这是输出：

[('Handsome', 'NNP'), ('Bob', 'NNP'), ("'s", 'POS'), ('dog', 'NN'), ('is', 'VBZ'), ('a', 'DT'), ('beautiful', 'JJ'), ('Chihuahua', 'NNP')]

我的问题是，显然TextBlob认为“帅”是一个单数专有名词，这是不正确的，因为“帅”应该是一个形容词。有没有办法解决这个问题，我也在NLTK上尝试过，但也得到了同样的结果。

Answer 1

之所以会发生这种情况，是因为causing的大写导致它被视为Bob名字的一部分。这不一定是一个不正确的分析，但如果你想强制进行形容词分析，你可以去掉下面的text2和text4中的“below”的大写。

text = "Handsome Bob's dog is a beautiful chihuahua"

BrinBot(text)
[('Handsome', 'NNP'), ('Bob', 'NNP'), ("'s", 'POS'), ('dog', 'NN'), ('is', 'VBZ'), ('a', 'DT'), ('beautiful', 'JJ'), ('Chihuahua', 'NNP')]

text2 = "handsome bob's dog is a beautiful chihuahua"

BrinBot(text2)
[('handsome', 'JJ'), ('bob', 'NN'), ("'s", 'POS'), ('dog', 'NN'), ('is', 'VBZ'), ('a', 'DT'), ('beautiful', 'JJ'), ('chihuahua', 'NN')]

text3 = "That beautiful chihuahua is handsome Bob's dog"

BrinBot(text3)
[('That', 'DT'), ('beautiful', 'JJ'), ('chihuahua', 'NN'), ('is', 'VBZ'), ('handsome', 'JJ'), ('Bob', 'NNP'), ("'s", 'POS'), ('dog', 'NN')]

text4 = "That beautiful chihuahua is Handsome Bob's dog"

BrinBot(text4)
[('That', 'DT'), ('beautiful', 'JJ'), ('chihuahua', 'NN'), ('is', 'VBZ'), ('Handsome', 'NNP'), ('Bob', 'NNP'), ("'s", 'POS'), ('dog', 'NN')]