单词列表的词形还原答案

【问题标题】：Lemmatization of a list of words单词列表的词形还原
【发布时间】：2016-03-07 15:29:18
【问题描述】：

所以我有一个文本文件中的单词列表。我想对它们进行词形还原以删除具有相同含义但时态不同的单词。喜欢尝试，尝试等。当我这样做时，我不断收到类似 TypeError: unhashable type: 'list' 的错误

    results=[]
    with open('/Users/xyz/Documents/something5.txt', 'r') as f:
       for line in f:
          results.append(line.strip().split())

    lemma= WordNetLemmatizer()

    lem=[]

    for r in results:
       lem.append(lemma.lemmatize(r))

    with open("lem.txt","w") as t:
      for item in lem:
        print>>t, item

如何对已经是标记的单词进行词形还原？

【问题讨论】：

标签： python nltk lemmatization

【解决方案1】：

WordNetLemmatizer.lemmatize 方法可能需要一个字符串，但您传递给它的是一个字符串列表。这给了你TypeError 异常。

line.split() 的结果是一个字符串列表，您将其作为列表附加到 results 即列表列表。

你想使用results.extend(line.strip().split())

results = []
with open('/Users/xyz/Documents/something5.txt', 'r') as f:
    for line in f:
        results.extend(line.strip().split())

lemma = WordNetLemmatizer()

lem = map(lemma.lemmatize, results)

with open("lem.txt", "w") as t:
    for item in lem:
        print >> t, item

或在没有中间结果列表的情况下进行重构

def words(fname):
    with open(fname, 'r') as document:
        for line in document:
            for word in line.strip().split():
                yield word

lemma = WordNetLemmatizer()
lem = map(lemma.lemmatize, words('/Users/xyz/Documents/something5.txt'))

【讨论】：

【解决方案2】：

Open a text file and and read lists as results as shown below
fo = open(filename)
results1 = fo.readlines()

results1
['I have a list of words in a text file', ' \n I want to perform lemmatization on them to remove words which have the same meaning but are in different tenses', '']

# Tokenize lists

results2 = [line.split() for line in results1]

# Remove empty lists

results2 = [ x for x in results2 if x != []]

# Lemmatize each word from a list using WordNetLemmatizer

from nltk.stem.wordnet import WordNetLemmatizer
lemmatizer = WordNetLemmatizer()
lemma_list_of_words = []
for i in range(0, len(results2)):
     l1 = results2[i]
     l2 = ' '.join([lemmatizer.lemmatize(word) for word in l1])
     lemma_list_of_words.append(l2)
lemma_list_of_words
['I have a list of word in a text file', 'I want to perform lemmatization on them to remove word which have the same meaning but are in different tense']

Please look at the lemmatized difference between lemma_list_of_words and results1.

【讨论】：