使用nltk.data.load加载english.pickle失败
使用nltk.data.load加载english.pickle失败
提问于 2011-02-02 03:43:49
尝试加载punkt标记器时...
import nltk.data
tokenizer = nltk.data.load('nltk:tokenizers/punkt/english.pickle')...a LookupError被提了出来：
> LookupError:
> *********************************************************************
> Resource 'tokenizers/punkt/english.pickle' not found. Please use the NLTK Downloader to obtain the resource: nltk.download(). Searched in:
> - 'C:\\Users\\Martinos/nltk_data'
> - 'C:\\nltk_data'
> - 'D:\\nltk_data'
> - 'E:\\nltk_data'
> - 'E:\\Python26\\nltk_data'
> - 'E:\\Python26\\lib\\nltk_data'
> - 'C:\\Users\\Martinos\\AppData\\Roaming\\nltk_data'
> **********************************************************************回答 15
Stack Overflow用户
发布于 2012-06-01 23:12:26
我也有同样的问题。进入python shell并输入：
>>> import nltk
>>> nltk.download()然后会出现一个安装窗口。转到'Models‘选项卡，并从'Identifier’列下选择'punkt‘。然后单击Download，它将安装必要的文件。那么它应该是有效的！
Stack Overflow用户
发布于 2014-12-30 21:50:10
你看到这个错误的主要原因是nltk找不到punkt包。由于nltk套件的大小，当用户安装它时，默认情况下并不会下载所有可用的软件包。
您可以像这样下载punkt包。
import nltk
nltk.download('punkt')
from nltk import word_tokenize,sent_tokenize在较新版本的错误消息中也建议这样做：
LookupError:
**********************************************************************
Resource punkt not found.
Please use the NLTK Downloader to obtain the resource:
>>> import nltk
>>> nltk.download('punkt')
Searched in:
- '/root/nltk_data'
- '/usr/share/nltk_data'
- '/usr/local/share/nltk_data'
- '/usr/lib/nltk_data'
- '/usr/local/lib/nltk_data'
- '/usr/nltk_data'
- '/usr/lib/nltk_data'
- ''
**********************************************************************如果不向download函数传递任何参数，它将下载所有包，即chunkers、grammars、misc、sentiment、taggers、corpora、help、models、<代码>D14、<代码>D15。
nltk.download()上面的函数将包保存到特定的目录。您可以在此处的注释中找到该目录位置。https://github.com/nltk/nltk/blob/67ad86524d42a3a86b1f5983868fd2990b59f1ba/nltk/downloader.py#L1051
Stack Overflow用户
发布于 2015-07-17 16:00:46
这就是刚才对我有效的方法：
# Do this in a separate python interpreter session, since you only have to do it once
import nltk
nltk.download('punkt')
# Do this in your ipython notebook or analysis script
from nltk.tokenize import word_tokenize
sentences = [
"Mr. Green killed Colonel Mustard in the study with the candlestick. Mr. Green is not a very nice fellow.",
"Professor Plum has a green plant in his study.",
"Miss Scarlett watered Professor Plum's green plant while he was away from his office last week."
]
sentences_tokenized = []
for s in sentences:
sentences_tokenized.append(word_tokenize(s))sentences_tokenized是令牌列表的列表：
[['Mr.', 'Green', 'killed', 'Colonel', 'Mustard', 'in', 'the', 'study', 'with', 'the', 'candlestick', '.', 'Mr.', 'Green', 'is', 'not', 'a', 'very', 'nice', 'fellow', '.'],
['Professor', 'Plum', 'has', 'a', 'green', 'plant', 'in', 'his', 'study', '.'],
['Miss', 'Scarlett', 'watered', 'Professor', 'Plum', "'s", 'green', 'plant', 'while', 'he', 'was', 'away', 'from', 'his', 'office', 'last', 'week', '.']]这些句子取自示例ipython notebook accompanying the book "Mining the Social Web, 2nd Edition"
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原文链接：
https://stackoverflow.com/questions/4867197
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