如何使用 NLTK 就地替换二元语法?

How to replace bigrams in place using NLTK?

假设我有一个元组列表,top_n,是文本语料库中最常见的 n 双字母组:

import nltk
from nltk import bigrams
from nltk import FreqDist

bi_grams = bigrams(text) # text is a list of strings (tokens)
fdistBigram = FreqDist(bi_grams)

n = 300
top_n= [list(t) for t in zip(*fdistBigram.most_common(n))][0]; top_n
>>> [('let', 'us'),
    ('us', 'know'),
    ('as', 'possible')
    ....

现在我想用 top_n 中的双字母词集替换 中的单词集实例。例如,假设我们有一个新变量 query,它是一个字符串列表:

query = ['please','let','us','know','as','soon','as','possible']

会变成

['please','letus', 'usknow', 'as', 'soon', 'aspossible']

在所需的操作之后。更明确地说,我想搜索 query 的每个元素并检查第 i 个和第 (i+1) 个元素是否在 top_n 中;如果是,则将 query[i]query[i+1] 替换为单个连接的二元语法,即 (query[i], query[i+1]) -> query[i] + query[i+1].

有没有什么方法可以使用 NLTK 来做到这一点,或者如果需要循环遍历 query 中的每个单词,最好的方法是什么?

鉴于您的代码和查询,如果单词在 top_n 中,它们将被贪婪地替换为它们的二元语法,这将达到目的:

lookup = set(top_n)  # {('let', 'us'), ('as', 'soon')}
query = ['please', 'let', 'us', 'know', 'as', 'soon', 'as', 'possible']
answer = []
q_iter = iter(range(len(query)))
for idx in q_iter:
    answer.append(query[idx])
    if idx < (len(query) - 1) and (query[idx], query[idx+1]) in lookup:
        answer[-1] += query[idx+1]
        next(q_iter)
        # if you don't want to skip over consumed 
        # second bi-gram elements and keep 
        # len(query) == len(answer), don't advance 
        # the iterator here, which also means you
        # don't have to create the iterator in outer scope

print(answer)

结果(例如):

>> ['please', 'letus', 'know', 'assoon', 'as', 'possible']

备选答案:

from gensim.models.phrases import Phraser
from gensim.models import Phrases
phrases = Phrases(text, min_count=1500, threshold=0.01)
bigram = Phraser(phrases)
bigram[query]
>>> ['please', 'let_us', 'know', 'as', 'soon', 'as', 'possible']

不完全是问题中所需的输出,但它可以作为替代方案。输入 min_countthreshold 将强烈影响输出。感谢 this question here.