Question

快速的问题令我感到困惑。我安装了NLTK，并且工作正常。然而，我试图得到一个语料库的bigrams并且想要基本上使用bigrams（语料库）..但它说当我从“来自nltk import bigrams”时没有定义bigrams

与三卦相同。我错过了什么吗？另外，我怎样才能手动从语料库中获取bigrams。

我也在计算bigrams三卦和四边形的频率，但我不确定如何解决这个问题。

我在开头和结尾处使用"<s>"和"</s>"标记了语料库。到目前为止的计划：

 #!/usr/bin/env python
import re
import nltk
import nltk.corpus as corpus
import tokenize
from nltk.corpus import brown

def alter_list(row):
    if row[-1] == '.':
        row[-1] = '</s>'
    else:
        row.append('</s>')
    return ['<s>'] + row

news = corpus.brown.sents(categories = 'editorial')
print len(news),'\n'

x = len(news)
for row in news[:x]:
    print(alter_list(row))

Answer 1

我在virtualenv中对此进行了测试，它确实有效：

In [20]: from nltk import bigrams

In [21]: bigrams('This is a test')
Out[21]: 
[('T', 'h'),
 ('h', 'i'),
 ('i', 's'),
 ('s', ' '),
 (' ', 'i'),
 ('i', 's'),
 ('s', ' '),
 (' ', 'a'),
 ('a', ' '),
 (' ', 't'),
 ('t', 'e'),
 ('e', 's'),
 ('s', 't')]

这是你唯一的错误吗？

顺便提一下，至于你的第二个问题：

from collections import Counter
In [44]: b = bigrams('This is a test')

In [45]: Counter(b)
Out[45]: Counter({('i', 's'): 2, ('s', ' '): 2, ('a', ' '): 1, (' ', 't'): 1, ('e', 's'): 1, ('h', 'i'): 1, ('t', 'e'): 1, ('T', 'h'): 1, (' ', 'i'): 1, (' ', 'a'): 1, ('s', 't'): 1})

对于单词：

In [49]: b = bigrams("This is a test".split(' '))

In [50]: b
Out[50]: [('This', 'is'), ('is', 'a'), ('a', 'test')]

In [51]: Counter(b)
Out[51]: Counter({('is', 'a'): 1, ('a', 'test'): 1, ('This', 'is'): 1})

这种分词显然是非常肤浅的，但根据你的应用，它可能就足够了。显然你可以使用更复杂的nltk的tokenize。

为了实现你的最终目标，你可以这样做：

In [56]: d = "Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum."

In [56]: from nltk import trigrams
In [57]: tri = trigrams(d.split(' '))

In [60]: counter = Counter(tri)

In [61]: import random

In [62]: random.sample(counter, 5)
Out[62]: 
[('Ipsum', 'has', 'been'),
 ('industry.', 'Lorem', 'Ipsum'),
 ('Ipsum', 'passages,', 'and'),
 ('was', 'popularised', 'in'),
 ('galley', 'of', 'type')]

我修剪了输出，因为它不必要地大，但你明白了。

无法从NLTK库导入Bigrams

1 个答案: