python类parse()的实例源码

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = Expression.fromstring(meaning)
        elif isinstance(meaning, Expression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def dep_parse(self, sentence):
        """
        Return a dependency graph for the sentence.

        :param sentence: the sentence to be parsed
        :type sentence: list(str)
        :rtype: DependencyGraph
        """

        #Lazy-initialize the depparser
        if self.depparser is None:
            from nltk.parse import MaltParser
            self.depparser = MaltParser(tagger=self.get_pos_tagger())
        if not self.depparser._trained:
            self.train_depparser()
        return self.depparser.parse(sentence, verbose=self.verbose)

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = drt.DrtExpression.fromstring(meaning)
        elif isinstance(meaning, drt.DrtExpression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = Expression.fromstring(meaning)
        elif isinstance(meaning, Expression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def dep_parse(self, sentence):
        """
        Return a dependency graph for the sentence.

        :param sentence: the sentence to be parsed
        :type sentence: list(str)
        :rtype: DependencyGraph
        """

        #Lazy-initialize the depparser
        if self.depparser is None:
            from nltk.parse import MaltParser
            self.depparser = MaltParser(tagger=self.get_pos_tagger())
        if not self.depparser._trained:
            self.train_depparser()
        return self.depparser.parse(sentence, verbose=self.verbose)

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = drt.DrtExpression.fromstring(meaning)
        elif isinstance(meaning, drt.DrtExpression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = Expression.fromstring(meaning)
        elif isinstance(meaning, Expression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def dep_parse(self, sentence):
        """
        Return a dependency graph for the sentence.

        :param sentence: the sentence to be parsed
        :type sentence: list(str)
        :rtype: DependencyGraph
        """

        #Lazy-initialize the depparser
        if self.depparser is None:
            from nltk.parse import MaltParser
            self.depparser = MaltParser(tagger=self.get_pos_tagger())
        if not self.depparser._trained:
            self.train_depparser()
        return self.depparser.parse(sentence, verbose=self.verbose)

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = drt.DrtExpression.fromstring(meaning)
        elif isinstance(meaning, drt.DrtExpression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = Expression.fromstring(meaning)
        elif isinstance(meaning, Expression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def dep_parse(self, sentence):
        """
        Return a dependency graph for the sentence.

        :param sentence: the sentence to be parsed
        :type sentence: list(str)
        :rtype: DependencyGraph
        """

        #Lazy-initialize the depparser
        if self.depparser is None:
            from nltk.parse import MaltParser
            self.depparser = MaltParser(tagger=self.get_pos_tagger())
        if not self.depparser._trained:
            self.train_depparser()
        return self.depparser.parse(sentence, verbose=self.verbose)

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = drt.DrtExpression.fromstring(meaning)
        elif isinstance(meaning, drt.DrtExpression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = Expression.fromstring(meaning)
        elif isinstance(meaning, Expression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = drt.DrtExpression.fromstring(meaning)
        elif isinstance(meaning, drt.DrtExpression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = Expression.fromstring(meaning)
        elif isinstance(meaning, Expression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def dep_parse(self, sentence):
        """
        Return a dependency graph for the sentence.

        :param sentence: the sentence to be parsed
        :type sentence: list(str)
        :rtype: DependencyGraph
        """

        #Lazy-initialize the depparser
        if self.depparser is None:
            from nltk.parse import MaltParser
            self.depparser = MaltParser(tagger=self.get_pos_tagger())
        if not self.depparser._trained:
            self.train_depparser()
        return self.depparser.parse(sentence, verbose=self.verbose)

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = drt.DrtExpression.fromstring(meaning)
        elif isinstance(meaning, drt.DrtExpression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = Expression.fromstring(meaning)
        elif isinstance(meaning, Expression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def dep_parse(self, sentence):
        """
        Return a dependency graph for the sentence.

        :param sentence: the sentence to be parsed
        :type sentence: list(str)
        :rtype: DependencyGraph
        """

        #Lazy-initialize the depparser
        if self.depparser is None:
            from nltk.parse import MaltParser
            self.depparser = MaltParser(tagger=self.get_pos_tagger())
        if not self.depparser._trained:
            self.train_depparser()
        return self.depparser.parse(sentence, verbose=self.verbose)

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = drt.DrtExpression.fromstring(meaning)
        elif isinstance(meaning, drt.DrtExpression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = Expression.fromstring(meaning)
        elif isinstance(meaning, Expression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def dep_parse(self, sentence):
        """
        Return a dependency graph for the sentence.

        :param sentence: the sentence to be parsed
        :type sentence: list(str)
        :rtype: DependencyGraph
        """

        #Lazy-initialize the depparser
        if self.depparser is None:
            from nltk.parse import MaltParser
            self.depparser = MaltParser(tagger=self.get_pos_tagger())
        if not self.depparser._trained:
            self.train_depparser()
        return self.depparser.parse(sentence, verbose=self.verbose)

def __init__(self, meaning, glue, indices=None):
        if not indices:
            indices = set()

        if isinstance(meaning, string_types):
            self.meaning = drt.DrtExpression.fromstring(meaning)
        elif isinstance(meaning, drt.DrtExpression):
            self.meaning = meaning
        else:
            raise RuntimeError('Meaning term neither string or expression: %s, %s' % (meaning, meaning.__class__))

        if isinstance(glue, string_types):
            self.glue = linearlogic.LinearLogicParser().parse(glue)
        elif isinstance(glue, linearlogic.Expression):
            self.glue = glue
        else:
            raise RuntimeError('Glue term neither string or expression: %s, %s' % (glue, glue.__class__))

        self.indices = indices

def demo(show_example=-1):
    from nltk.parse import MaltParser
    examples = ['David sees Mary',
                'David eats a sandwich',
                'every man chases a dog',
                'every man believes a dog sleeps',
                'John gives David a sandwich',
                'John chases himself']
#                'John persuades David to order a pizza',
#                'John tries to go',
#                'John tries to find a unicorn',
#                'John seems to vanish',
#                'a unicorn seems to approach',
#                'every big cat leaves',
#                'every gray cat leaves',
#                'every big gray cat leaves',
#                'a former senator leaves',

    print('============== DEMO ==============')

    tagger = RegexpTagger(
        [('^(David|Mary|John)$', 'NNP'),
         ('^(sees|eats|chases|believes|gives|sleeps|chases|persuades|tries|seems|leaves)$', 'VB'),
         ('^(go|order|vanish|find|approach)$', 'VB'),
         ('^(a)$', 'ex_quant'),
         ('^(every)$', 'univ_quant'),
         ('^(sandwich|man|dog|pizza|unicorn|cat|senator)$', 'NN'),
         ('^(big|gray|former)$', 'JJ'),
         ('^(him|himself)$', 'PRP')
    ])

    depparser = MaltParser(tagger=tagger)
    glue = Glue(depparser=depparser, verbose=False)

    for (i, sentence) in enumerate(examples):
        if i==show_example or show_example==-1:
            print('[[[Example %s]]]  %s' % (i, sentence))
            for reading in glue.parse_to_meaning(sentence.split()):
                print(reading.simplify())
            print('')

def demo(show_example=-1):
    from nltk.parse import MaltParser
    examples = ['David sees Mary',
                'David eats a sandwich',
                'every man chases a dog',
                'every man believes a dog sleeps',
                'John gives David a sandwich',
                'John chases himself']
#                'John persuades David to order a pizza',
#                'John tries to go',
#                'John tries to find a unicorn',
#                'John seems to vanish',
#                'a unicorn seems to approach',
#                'every big cat leaves',
#                'every gray cat leaves',
#                'every big gray cat leaves',
#                'a former senator leaves',

    print('============== DEMO ==============')

    tagger = RegexpTagger(
        [('^(David|Mary|John)$', 'NNP'),
         ('^(sees|eats|chases|believes|gives|sleeps|chases|persuades|tries|seems|leaves)$', 'VB'),
         ('^(go|order|vanish|find|approach)$', 'VB'),
         ('^(a)$', 'ex_quant'),
         ('^(every)$', 'univ_quant'),
         ('^(sandwich|man|dog|pizza|unicorn|cat|senator)$', 'NN'),
         ('^(big|gray|former)$', 'JJ'),
         ('^(him|himself)$', 'PRP')
    ])

    depparser = MaltParser(tagger=tagger)
    glue = Glue(depparser=depparser, verbose=False)

    for (i, sentence) in enumerate(examples):
        if i==show_example or show_example==-1:
            print('[[[Example %s]]]  %s' % (i, sentence))
            for reading in glue.parse_to_meaning(sentence.split()):
                print(reading.simplify())
            print('')

def demo(show_example=-1):
    from nltk.parse import MaltParser
    examples = ['David sees Mary',
                'David eats a sandwich',
                'every man chases a dog',
                'every man believes a dog sleeps',
                'John gives David a sandwich',
                'John chases himself']
#                'John persuades David to order a pizza',
#                'John tries to go',
#                'John tries to find a unicorn',
#                'John seems to vanish',
#                'a unicorn seems to approach',
#                'every big cat leaves',
#                'every gray cat leaves',
#                'every big gray cat leaves',
#                'a former senator leaves',

    print('============== DEMO ==============')

    tagger = RegexpTagger(
        [('^(David|Mary|John)$', 'NNP'),
         ('^(sees|eats|chases|believes|gives|sleeps|chases|persuades|tries|seems|leaves)$', 'VB'),
         ('^(go|order|vanish|find|approach)$', 'VB'),
         ('^(a)$', 'ex_quant'),
         ('^(every)$', 'univ_quant'),
         ('^(sandwich|man|dog|pizza|unicorn|cat|senator)$', 'NN'),
         ('^(big|gray|former)$', 'JJ'),
         ('^(him|himself)$', 'PRP')
    ])

    depparser = MaltParser(tagger=tagger)
    glue = Glue(depparser=depparser, verbose=False)

    for (i, sentence) in enumerate(examples):
        if i==show_example or show_example==-1:
            print('[[[Example %s]]]  %s' % (i, sentence))
            for reading in glue.parse_to_meaning(sentence.split()):
                print(reading.simplify())
            print('')

def demo(show_example=-1):
    from nltk.parse import MaltParser
    examples = ['David sees Mary',
                'David eats a sandwich',
                'every man chases a dog',
                'every man believes a dog sleeps',
                'John gives David a sandwich',
                'John chases himself']
#                'John persuades David to order a pizza',
#                'John tries to go',
#                'John tries to find a unicorn',
#                'John seems to vanish',
#                'a unicorn seems to approach',
#                'every big cat leaves',
#                'every gray cat leaves',
#                'every big gray cat leaves',
#                'a former senator leaves',

    print('============== DEMO ==============')

    tagger = RegexpTagger(
        [('^(David|Mary|John)$', 'NNP'),
         ('^(sees|eats|chases|believes|gives|sleeps|chases|persuades|tries|seems|leaves)$', 'VB'),
         ('^(go|order|vanish|find|approach)$', 'VB'),
         ('^(a)$', 'ex_quant'),
         ('^(every)$', 'univ_quant'),
         ('^(sandwich|man|dog|pizza|unicorn|cat|senator)$', 'NN'),
         ('^(big|gray|former)$', 'JJ'),
         ('^(him|himself)$', 'PRP')
    ])

    depparser = MaltParser(tagger=tagger)
    glue = Glue(depparser=depparser, verbose=False)

    for (i, sentence) in enumerate(examples):
        if i==show_example or show_example==-1:
            print('[[[Example %s]]]  %s' % (i, sentence))
            for reading in glue.parse_to_meaning(sentence.split()):
                print(reading.simplify())
            print('')

def dep_parse(self, sentence):
        #Lazy-initialize the depparser
        if self.depparser is None:
            from nltk.parse import MaltParser
            self.depparser = MaltParser(tagger=self.get_pos_tagger())
        if not self.depparser._trained:
            self.train_depparser()
        return [self.depparser.parse(sentence, verbose=self.verbose)]

def demo(show_example=-1):
    from nltk.parse import MaltParser
    examples = ['David sees Mary',
                'David eats a sandwich',
                'every man chases a dog',
                'every man believes a dog sleeps',
                'John gives David a sandwich',
                'John chases himself']
#                'John persuades David to order a pizza',
#                'John tries to go',
#                'John tries to find a unicorn',
#                'John seems to vanish',
#                'a unicorn seems to approach',
#                'every big cat leaves',
#                'every gray cat leaves',
#                'every big gray cat leaves',
#                'a former senator leaves',

    print('============== DEMO ==============')

    tagger = RegexpTagger(
        [('^(David|Mary|John)$', 'NNP'),
         ('^(sees|eats|chases|believes|gives|sleeps|chases|persuades|tries|seems|leaves)$', 'VB'),
         ('^(go|order|vanish|find|approach)$', 'VB'),
         ('^(a)$', 'ex_quant'),
         ('^(every)$', 'univ_quant'),
         ('^(sandwich|man|dog|pizza|unicorn|cat|senator)$', 'NN'),
         ('^(big|gray|former)$', 'JJ'),
         ('^(him|himself)$', 'PRP')
    ])

    depparser = MaltParser(tagger=tagger)
    glue = Glue(depparser=depparser, verbose=False)

    for (i, sentence) in enumerate(examples):
        if i==show_example or show_example==-1:
            print('[[[Example %s]]]  %s' % (i, sentence))
            for reading in glue.parse_to_meaning(sentence.split()):
                print(reading.simplify())
            print('')

def demo(show_example=-1):
    from nltk.parse import MaltParser
    examples = ['David sees Mary',
                'David eats a sandwich',
                'every man chases a dog',
                'every man believes a dog sleeps',
                'John gives David a sandwich',
                'John chases himself']
#                'John persuades David to order a pizza',
#                'John tries to go',
#                'John tries to find a unicorn',
#                'John seems to vanish',
#                'a unicorn seems to approach',
#                'every big cat leaves',
#                'every gray cat leaves',
#                'every big gray cat leaves',
#                'a former senator leaves',

    print('============== DEMO ==============')

    tagger = RegexpTagger(
        [('^(David|Mary|John)$', 'NNP'),
         ('^(sees|eats|chases|believes|gives|sleeps|chases|persuades|tries|seems|leaves)$', 'VB'),
         ('^(go|order|vanish|find|approach)$', 'VB'),
         ('^(a)$', 'ex_quant'),
         ('^(every)$', 'univ_quant'),
         ('^(sandwich|man|dog|pizza|unicorn|cat|senator)$', 'NN'),
         ('^(big|gray|former)$', 'JJ'),
         ('^(him|himself)$', 'PRP')
    ])

    depparser = MaltParser(tagger=tagger)
    glue = Glue(depparser=depparser, verbose=False)

    for (i, sentence) in enumerate(examples):
        if i==show_example or show_example==-1:
            print('[[[Example %s]]]  %s' % (i, sentence))
            for reading in glue.parse_to_meaning(sentence.split()):
                print(reading.simplify())
            print('')