使用 pattern.en 格式化整个文本？

Question

出于机器学习的目的，我需要分析一些文本。我认识的一位数据科学家建议我为我的项目使用 pattern.en。

我会给我的程序一个关键字（示例 : pizza），它必须从我给他的几个文本中排序一些"trends"。（示例：我给他一些关于比萨饼上的花生酱的文本，所以程序会识别花生酱是一种增长趋势。）

所以首先，我必须 "clean" 文本。我知道 pattern.en 可以将单词识别为名词、动词、副词等，我想删除所有限定词、冠词和其他 "meaningless" 词以进行分析，但我不知道该怎么做。我尝试 parse() 所以我可以得到 :

s = "Hello, how is it going ? I am tired actually, did not sleep enough... That is bad for work, definitely"
parsedS = parse(s)
print(parsedS)

输出：

Hello/UH/hello ,/,/, how/WRB/how is/VBZ/be it/PRP/it going/VBG/go ?/./?
I/PRP/i am/VBP/be tired/VBN/tire actually/RB/actually ,/,/, did/VBD/do not/RB/not sleep/VB/sleep enough/RB/enough .../:/...
That/DT/that is/VBZ/be bad/JJ/bad for/IN/for work/NN/work ,/,/, definitely/RB/definitely

所以我想删除带有标签 "UH"、","、"PRP" 等的单词，但我不知道该怎么做，并且不会弄乱句子 (出于分析目的，我将忽略 Example)

中没有单词 "pizza" 的句子

不知道我解释的清楚了没有，有什么不明白的可以问我

编辑 - 更新： 在 canyon289 的回答之后，我想逐句进行，而不是针对整个文本.我试过了：

for sentence in Text(s):
    sentence = sentence.split(" ")
    print("SENTENCE :")
    for word in sentence:
        if not any(tag in word for tag in dont_want):
            print(word)

但是我有以下错误:

AttributeError: 'Sentence' object has no attribute 'split'

我该如何解决这个问题？

Answer 1

这应该适合你

s = "Hello, how is it going ? I am tired actually, did not sleep   enough... That is bad for work, definitely"
s = parse(s)

#Create a list of all the tags you don't want
dont_want = ["UH", "PRP"]

sentence = parse(s).split(" ")

#Go through all the words and look for any occurence of the tag you don't want
#This is done through a nested list comprehension
[word for word in sentence if not any(tag in word for tag in dont_want)]

[u',/,/O/O', u'how/WRB/O/O', u'is/VBZ/B-VP/O', u'going/VBG/B-VP/O', u'am/VBP/B-VP/O', u'tired/VBN/I-VP/O', u'actually/RB/B-ADVP/O', u',/,/O/O', u'did/VBD/B-VP/O', u'not/RB/I-VP/O', u'sleep/VB/I-VP/O', u'enough/RB/B-ADVP/O', u'.../:/O/O\nThat/DT/O/O', u'is/VBZ/B-VP/O', u'bad/JJ/B-ADJP/O', u'for/IN/B-PP/B-PNP', u'work/NN/B-NP/I-PNP', u',/,/O/O', u'definitely/RB/B-ADVP/O']

使用 pattern.en 格式化整个文本？

Format an entire text with pattern.en?

python

nlp

machine-learning