NLTK在荷兰命名实体识别 [英] NLTK named entity recognition in dutch

查看:91
本文介绍了NLTK在荷兰命名实体识别的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我正在尝试从荷兰文字中提取命名实体.我使用 nltk-trainer 来在conll2002荷兰语料库上训练标记器和分块器.但是,来自分块器的parse方法未检测到任何命名实体.这是我的代码:

I am trying to extract named entities from dutch text. I used nltk-trainer to train a tagger and a chunker on the conll2002 dutch corpus. However, the parse method from the chunker is not detecting any named entities. Here is my code:

str = 'Christiane heeft een lam.'

tagger = nltk.data.load('taggers/dutch.pickle')
chunker = nltk.data.load('chunkers/dutch.pickle')

str_tags = tagger.tag(nltk.word_tokenize(str))
print str_tags

str_chunks = chunker.parse(str_tags)
print str_chunks

该程序的输出:

[('Christiane', u'N'), ('heeft', u'V'), ('een', u'Art'), ('lam', u'Adj'), ('.', u'Punc')]
(S Christiane/N heeft/V een/Art lam/Adj ./Punc)

我希望克里斯蒂安妮被视作一个命名实体. 有帮助吗?

I was expecting Christiane to be detected as a named entity. Any help?

推荐答案

conll2002语料库同时具有西班牙语和荷兰语文本,因此应确保使用fileids参数,如python train_chunker.py conll2002 --fileids ned.train所示.西班牙语和荷兰语的培训都不会取得很好的效果.

The conll2002 corpus has both spanish and dutch text, so you should make sure to use the fileids parameter, as in python train_chunker.py conll2002 --fileids ned.train. Training on both spanish and dutch will have poor results.

默认算法是基于Tagger的Chunker,在conll2002上效果不佳.而是使用像NaiveBayes这样的基于分类器的分块器,这样完整的命令可能看起来像这样(并且我已经确认生成的分块器确实将"Christiane"识别为"PER"):

The default algorithm is a Tagger based Chunker, which does not work well on conll2002. Instead, use a classifier based chunker like NaiveBayes, so the full command might look like this (and I've confirmed that the resulting chunker does recognize "Christiane" as a "PER"):

python train_chunker.py conll2002 --fileids ned.train --classifier NaiveBayes --filename ~/nltk_data/chunkers/conll2002_ned_NaiveBayes.pickle

这篇关于NLTK在荷兰命名实体识别的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

查看全文
登录 关闭
扫码关注1秒登录
发送“验证码”获取 | 15天全站免登陆