2015-01-09 84 views

回答

4

总之:是的,它是可能的,但你会在痛苦的赫克得到的,它更容易使用atis.cfg作为基础,然后读取新的文本文件CFG重写你的CFG。它更容易,而不是重新分配每一个新的终端,以正确的非终端映射它们


在长,请参阅以下

首先,让我们看看在NLTK一个CFG语法是什么,它包含:

>>> 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'] 

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

好像端子和非终端是Production类型,参见https://github.com/nltk/nltk/blob/develop/nltk/grammar.py#L236,即

语法生成。每个生产将“左侧”上的一个符号 映射到“右侧”上的符号序列上。 (在上下文无关的情况下, 的左侧必须是Nonterminal,右侧的 一侧是一系列终端,Nonterminals。) “终端”可以是任何不可变的可哈希对象,即 不是Nonterminal。通常,终端是表示单词的字符串 ,例如"dog""under"

那么让我们来看看语法如何存储的作品:

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

所以,现在,好像我们只能创建nltk.grammar.Production对象,并把它们添加到grammar._productions

让我们尝试与原来的语法:

>>> 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 .))) 

原来的语法不具备终端singapore

>>> 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'". 

之前,我们尝试添加singapore到语法,让我们看看如何detroit存储在语法中:

>>> 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重新创建singapore相同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) 

但它仍然没有工作,但导致给终端本身并不真正帮助它涉及到CFG,因此新加坡的休息仍然没有语法分析:

>>> 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,新加坡是像底特律和底特律导致这个左handside LHS NOUN_NP -> detroit

>>> 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,要么添加另一个生产为新加坡,导致NOUN_NP终结符号或我们的新加坡LHS追加到NOUN_NP非终结符右手边:

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

现在让我们添加新的生产NOUN_NP -> singapore

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

现在我们应该期待我们的解析器可以工作:

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'". 

但它看起来像语法仍然没有认识到我们已经添加了新的终端和非终结符,所以让我们尝试一个黑客和输出我们的新的语法转换为字符串,并创建一个新的语法从输出字符串:

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 .))) 
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