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现在,NLTK中有一个更稳定的MaltParser API版本:https://github.com/nltk/nltk/pull/944,但是在同时解析多个句子时存在问题。
一次解析一个句子似乎没问题:
_path_to_maltparser = '/home/alvas/maltparser-1.8/dist/maltparser-1.8/'
_path_to_model= '/home/alvas/engmalt.linear-1.7.mco'
>>> mp = MaltParser(path_to_maltparser=_path_to_maltparser, model=_path_to_model)
>>> sent = 'I shot an elephant in my pajamas'.split()
>>> sent2 = 'Time flies like banana'.split()
>>> print(mp.parse_one(sent).tree())
(pajamas (shot I) an elephant in my)
但是解析句子列表并不会返回DependencyGraph对象:
_path_to_maltparser = '/home/alvas/maltparser-1.8/dist/maltparser-1.8/'
_path_to_model= '/home/alvas/engmalt.linear-1.7.mco'
>>> mp = MaltParser(path_to_maltparser=_path_to_maltparser, model=_path_to_model)
>>> sent = 'I shot an elephant in my pajamas'.split()
>>> sent2 = 'Time flies like banana'.split()
>>> print(mp.parse_one(sent).tree())
(pajamas (shot I) an elephant in my)
>>> print(next(mp.parse_sents([sent,sent2])))
<listiterator object at 0x7f0a2e4d3d90>
>>> print(next(next(mp.parse_sents([sent,sent2]))))
[{u'address': 0,
u'ctag': u'TOP',
u'deps': [2],
u'feats': None,
u'lemma': None,
u'rel': u'TOP',
u'tag': u'TOP',
u'word': None},
{u'address': 1,
u'ctag': u'NN',
u'deps': [],
u'feats': u'_',
u'head': 2,
u'lemma': u'_',
u'rel': u'nn',
u'tag': u'NN',
u'word': u'I'},
{u'address': 2,
u'ctag': u'NN',
u'deps': [1, 11],
u'feats': u'_',
u'head': 0,
u'lemma': u'_',
u'rel': u'null',
u'tag': u'NN',
u'word': u'shot'},
{u'address': 3,
u'ctag': u'AT',
u'deps': [],
u'feats': u'_',
u'head': 11,
u'lemma': u'_',
u'rel': u'nn',
u'tag': u'AT',
u'word': u'an'},
{u'address': 4,
u'ctag': u'NN',
u'deps': [],
u'feats': u'_',
u'head': 11,
u'lemma': u'_',
u'rel': u'nn',
u'tag': u'NN',
u'word': u'elephant'},
{u'address': 5,
u'ctag': u'NN',
u'deps': [],
u'feats': u'_',
u'head': 11,
u'lemma': u'_',
u'rel': u'nn',
u'tag': u'NN',
u'word': u'in'},
{u'address': 6,
u'ctag': u'NN',
u'deps': [],
u'feats': u'_',
u'head': 11,
u'lemma': u'_',
u'rel': u'nn',
u'tag': u'NN',
u'word': u'my'},
{u'address': 7,
u'ctag': u'NNS',
u'deps': [],
u'feats': u'_',
u'head': 11,
u'lemma': u'_',
u'rel': u'nn',
u'tag': u'NNS',
u'word': u'pajamas'},
{u'address': 8,
u'ctag': u'NN',
u'deps': [],
u'feats': u'_',
u'head': 11,
u'lemma': u'_',
u'rel': u'nn',
u'tag': u'NN',
u'word': u'Time'},
{u'address': 9,
u'ctag': u'NNS',
u'deps': [],
u'feats': u'_',
u'head': 11,
u'lemma': u'_',
u'rel': u'nn',
u'tag': u'NNS',
u'word': u'flies'},
{u'address': 10,
u'ctag': u'NN',
u'deps': [],
u'feats': u'_',
u'head': 11,
u'lemma': u'_',
u'rel': u'nn',
u'tag': u'NN',
u'word': u'like'},
{u'address': 11,
u'ctag': u'NN',
u'deps': [3, 4, 5, 6, 7, 8, 9, 10],
u'feats': u'_',
u'head': 2,
u'lemma': u'_',
u'rel': u'dep',
u'tag': u'NN',
u'word': u'banana'}]
为什么使用parse_sents()
不能返回parse_one
的可迭代对象?
不过,我可以选择变得懒惰并这样做:
_path_to_maltparser = '/home/alvas/maltparser-1.8/dist/maltparser-1.8/'
_path_to_model= '/home/alvas/engmalt.linear-1.7.mco'
>>> mp = MaltParser(path_to_maltparser=_path_to_maltparser, model=_path_to_model)
>>> sent1 = 'I shot an elephant in my pajamas'.split()
>>> sent2 = 'Time flies like banana'.split()
>>> sentences = [sent1, sent2]
>>> for sent in sentences:
>>> ... print(mp.parse_one(sent).tree())
但这不是我正在寻找的解决方案。我的问题是如何回答为什么
parse_sent()
不返回一个可迭代的parse_one()
,以及如何在NLTK代码中修复它?
在@NikitaAstrakhantsev回答后,我尝试了一下,现在它输出了一棵解析树,但似乎混淆了两个句子并将其合并成一个进行解析。
# Initialize a MaltParser object with a pre-trained model.
mp = MaltParser(path_to_maltparser=path_to_maltparser, model=path_to_model)
sent = 'I shot an elephant in my pajamas'.split()
sent2 = 'Time flies like banana'.split()
# Parse a single sentence.
print(mp.parse_one(sent).tree())
print(next(next(mp.parse_sents([sent,sent2]))).tree())
[out]:
(pajamas (shot I) an elephant in my)
(shot I (banana an elephant in my pajamas Time flies like))
从代码上看,它似乎在对两个句子进行解析之前做了一些奇怪的操作:https://github.com/nltk/nltk/blob/develop/nltk/parse/api.py#L45
NLTK中的解析器抽象类在解析之前将两个句子合并为一个,这是为什么呢?我是否错误地调用了parse_sents()
?如果是这样,正确的调用方式是什么?
yield '\n\n'
的缩进错了!!!天啊... - alvas