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python – NLTK：我可以将终端添加到已经生成的语法中

2019-05-19 23:47:03 作者：互联网

我已经从atis语法生成语法,现在我想添加一些我自己的规则,特别是句子中的终端可以这样做吗？

import nltk
grammar = nltk.data.load('grammars/large_grammars/atis.cfg')

语法我想添加更多的终端.

解决方法:

简而言之：是的,它是可能的,但你会遇到痛苦,使用atis.cfg作为基础重写CFG更容易,然后阅读新的CFG文本文件.将每个新终端重新分配到正确的非终端以映射它们比这更容易

不久,请参阅以下内容

首先让我们看看NLTK中的CFG语法是什么以及它包含的内容：

>>> import nltk
>>> g = nltk.data.load('grammars/large_grammars/atis.cfg')
>>> dir(g)
['__class__', '__delattr__', '__dict__', '__doc__', '__format__', '__getattribute__', '__hash__', '__init__', '__module__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__unicode__', '__weakref__', '_all_unary_are_lexical', '_calculate_grammar_forms', '_calculate_indexes', '_calculate_leftcorners', '_categories', '_empty_index', '_immediate_leftcorner_categories', '_immediate_leftcorner_words', '_is_lexical', '_is_nonlexical', '_leftcorner_parents', '_leftcorner_words', '_leftcorners', '_lexical_index', '_lhs_index', '_max_len', '_min_len', '_productions', '_rhs_index', '_start', 'check_coverage', 'fromstring', 'is_binarised', 'is_chomsky_normal_form', 'is_flexible_chomsky_normal_form', 'is_leftcorner', 'is_lexical', 'is_nonempty', 'is_nonlexical', 'leftcorner_parents', 'leftcorners', 'max_len', 'min_len', 'productions', 'start', 'unicode_repr']

有关更多详细信息,请参阅https://github.com/nltk/nltk/blob/develop/nltk/grammar.py#L421

似乎终端和非终端都是生产类型,见https://github.com/nltk/nltk/blob/develop/nltk/grammar.py#L236,即

A grammar production. Each production maps a single symbol
on the “left-hand side” to a sequence of symbols on the
“right-hand side”. (In the case of context-free productions,
the left-hand side must be a Nonterminal, and the right-hand
side is a sequence of terminals and Nonterminals.)
“terminals” can be any immutable hashable object that is
not a Nonterminal. Typically, terminals are strings
representing words, such as "dog" or "under".

那么让我们来看看语法如何存储产品：

>>> type(g._productions)
<type 'list'>
>>> g._productions[-1]
zero -> 'zero'
>>> type(g._productions[-1])
<class 'nltk.grammar.Production'>

所以现在,我们似乎可以创建nltk.grammar.Production对象并将它们附加到grammar._productions.

让我们试试原始语法：

>>> import nltk
>>> original_grammar = nltk.data.load('grammars/large_grammars/atis.cfg')
>>> original_parser = ChartParser(original_grammar)
>>> sent = ['show', 'me', 'northwest', 'flights', 'to', 'detroit', '.']
>>> for i in original_parser.parse(sent):
...     print i
...     break
... 
(SIGMA
  (IMPR_VB
    (VERB_VB (show show))
    (NP_PPO
      (pt_pron_ppo me)
      (NAPPOS_NP (NOUN_NP (northwest northwest))))
    (NP_NNS (NOUN_NNS (pt207 flights)) (PREP_IN (to to)))
    (AVPNP_NP (NOUN_NP (detroit detroit)))
    (pt_char_per .)))

原语法没有终端新加坡：

>>> sent = ['show', 'me', 'northwest', 'flights', 'to', 'singapore', '.']
>>> for i in original_parser.parse(sent):
...     print i
...     break
... 
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.7/dist-packages/nltk/parse/api.py", line 49, in parse
    return iter(self.parse_all(sent))
  File "/usr/local/lib/python2.7/dist-packages/nltk/parse/chart.py", line 1350, in parse_all
    chart = self.chart_parse(tokens)
  File "/usr/local/lib/python2.7/dist-packages/nltk/parse/chart.py", line 1309, in chart_parse
    self._grammar.check_coverage(tokens)
  File "/usr/local/lib/python2.7/dist-packages/nltk/grammar.py", line 631, in check_coverage
    "input words: %r." % missing)
ValueError: Grammar does not cover some of the input words: u"'singapore'".

在我们尝试将新加坡添加到语法中之前,让我们看看底层语是如何存储在语法中的：

>>> original_grammar._rhs_index['detroit']
[detroit -> 'detroit']
>>> type(original_grammar._rhs_index['detroit'])
<type 'list'>
>>> type(original_grammar._rhs_index['detroit'][0])
<class 'nltk.grammar.Production'>
>>> original_grammar._rhs_index['detroit'][0]._lhs
detroit
>>> original_grammar._rhs_index['detroit'][0]._rhs
(u'detroit',)
>>> type(original_grammar._rhs_index['detroit'][0]._lhs)
<class 'nltk.grammar.Nonterminal'>
>>> type(original_grammar._rhs_index['detroit'][0]._rhs)
<type 'tuple'>
>>> original_grammar._rhs_index[original_grammar._rhs_index['detroit'][0]._lhs]
[NOUN_NP -> detroit, NOUN_NP -> detroit minneapolis toronto]

所以现在我们可以尝试为新加坡重建相同的Production对象：

# First let's create Non-terminal for singapore.
>>> nltk.grammar.Nonterminal('singapore')
singapore
>>> lhs = nltk.grammar.Nonterminal('singapore')
>>> rhs = [u'singapore']
# Now we can create the Production for singapore.
>>> singapore_production = nltk.grammar.Production(lhs, rhs)
# Now let's try to add this Production the grammar's list of production
>>> new_grammar = nltk.data.load('grammars/large_grammars/atis.cfg')
>>> new_grammar._productions.append(singapore_production)

但它仍然无法正常工作,但导致终端本身并没有真正帮助将其与其余的CFG联系起来,因此新加坡仍然无法解析：

>>> new_grammar = nltk.data.load('grammars/large_grammars/atis.cfg')
>>> new_grammar._productions.append(singapore_production)
>>> new_parser = ChartParser(new_grammar)
>>> sent = ['show', 'me', 'northwest', 'flights', 'to', 'singapore', '.']
>>> new_parser.parse(sent)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.7/dist-packages/nltk/parse/api.py", line 49, in parse
    return iter(self.parse_all(sent))
  File "/usr/local/lib/python2.7/dist-packages/nltk/parse/chart.py", line 1350, in parse_all
    chart = self.chart_parse(tokens)
  File "/usr/local/lib/python2.7/dist-packages/nltk/parse/chart.py", line 1309, in chart_parse
    self._grammar.check_coverage(tokens)
  File "/usr/local/lib/python2.7/dist-packages/nltk/grammar.py", line 631, in check_coverage
    "input words: %r." % missing)
ValueError: Grammar does not cover some of the input words: u"'singapore'".

从下面我们知道新加坡就像底特律,底特律导致这个左手LHS NOUN_NP – >底特律：

>>> original_grammar._rhs_index[original_grammar._rhs_index['detroit'][0]._lhs]
[NOUN_NP -> detroit, NOUN_NP -> detroit minneapolis toronto]

所以我们需要做的是为新加坡添加另一个导致NOUN_NP非终结者的作品,或者将我们的新加坡LHS添加到NOUN_NP非终端右侧：

>>> lhs = nltk.grammar.Nonterminal('singapore')
>>> rhs = [u'singapore']
>>> singapore_production = nltk.grammar.Production(lhs, rhs)
>>> new_grammar._productions.append(singapore_production)

现在让我们为NOUN_NP添加新的作品 – >新加坡：

lhs2 = nltk.grammar.Nonterminal('NOUN_NP')
new_grammar._productions.append(nltk.grammar.Production(lhs2, [lhs]))

现在我们应该期望我们的解析器工作：

sent = ['show', 'me', 'northwest', 'flights', 'to', 'singapore', '.']
print new_grammar.productions()[2091]
print new_grammar.productions()[-1]
new_parser = nltk.ChartParser(new_grammar)
for i in new_parser.parse(sent):
    print i

[OUT]：

Traceback (most recent call last):
  File "test.py", line 31, in <module>
    for i in new_parser.parse(sent):
  File "/usr/local/lib/python2.7/dist-packages/nltk/parse/api.py", line 49, in parse
    return iter(self.parse_all(sent))
  File "/usr/local/lib/python2.7/dist-packages/nltk/parse/chart.py", line 1350, in parse_all
    chart = self.chart_parse(tokens)
  File "/usr/local/lib/python2.7/dist-packages/nltk/parse/chart.py", line 1309, in chart_parse
    self._grammar.check_coverage(tokens)
  File "/usr/local/lib/python2.7/dist-packages/nltk/grammar.py", line 631, in check_coverage
    "input words: %r." % missing)
ValueError: Grammar does not cover some of the input words: u"'singapore'".

但看起来语法仍然没有识别我们添加的新终端和非终端,所以让我们尝试一下hack并将我们的新语法输出到字符串中并从输出字符串创建一个更新的语法：

import nltk

lhs = nltk.grammar.Nonterminal('singapore')
rhs = [u'singapore']
singapore_production = nltk.grammar.Production(lhs, rhs)
new_grammar = nltk.data.load('grammars/large_grammars/atis.cfg')
new_grammar._productions.append(singapore_production)    
lhs2 = nltk.grammar.Nonterminal('NOUN_NP')
new_grammar._productions.append(nltk.grammar.Production(lhs2, [lhs]))

# Create newer grammar from new_grammar's string
newer_grammar =  nltk.grammar.CFG.fromstring(str(new_grammar).split('\n')[1:])
# Reassign new_grammar's string to newer_grammar !!!
newer_grammar._start = new_grammar.start()
newer_grammar
sent = ['show', 'me', 'northwest', 'flights', 'to', 'singapore', '.']
print newer_grammar.productions()[2091]
print newer_grammar.productions()[-1]
newer_parser = nltk.ChartParser(newer_grammar)
for i in newer_parser.parse(sent):
    print i
    break

[OUT]：

(SIGMA
  (IMPR_VB
    (VERB_VB (show show))
    (NP_PPO
      (pt_pron_ppo me)
      (NAPPOS_NP (NOUN_NP (northwest northwest))))
    (NP_NNS (NOUN_NNS (pt207 flights)) (PREP_IN (to to)))
    (AVPNP_NP (NOUN_NP (singapore singapore)))
    (pt_char_per .)))

标签：python,nlp,nltk,context-free-grammar
来源： https://codeday.me/bug/20190519/1138355.html