def tag_sentences(self, text, hyp, verbose=False):
        """
        Tag a RTEPair as to whether the hypothesis can be inferred from the text.
        """
        glueclass = DrtGlue()
        text_drs_list = glueclass.parse_to_meaning(text)
        if text_drs_list:
            text_ex = text_drs_list[0].simplify().toFol()
        else:
            if verbose: print 'ERROR: No readings were generated for the Text'
        
        hyp_drs_list = glueclass.parse_to_meaning(hyp)
        if hyp_drs_list:
            hyp_ex = hyp_drs_list[0].simplify().toFol()
        else:
            if verbose: print 'ERROR: No readings were generated for the Hypothesis'

        #1. proof T -> H
        #2. proof (BK & T) -> H
        #3. proof :(BK & T)
        #4. proof :(BK & T & H)
        #5. satisfy BK & T
        #6. satisfy BK & T & H
            
        result = inference.Prover9().prove(hyp_ex, [text_ex])
        if verbose: print 'prove: T -> H: %s' % result
        
        if not result:
            bk = self._generate_BK(text, hyp, verbose)
            bk_exs = [bk_pair[0] for bk_pair in bk]
            
            if verbose: 
                print 'Generated Background Knowledge:'
                for bk_ex in bk_exs:
                    print bk_ex
                
            result = inference.Prover9().prove(hyp_ex, [text_ex]+bk_exs)
            if verbose: print 'prove: (T & BK) -> H: %s' % result
            
            if not result:
                consistent = self.check_consistency(bk_exs+[text_ex])                
                if verbose: print 'consistency check: (BK & T): %s' % consistent

                if consistent:
                    consistent = self.check_consistency(bk_exs+[text_ex, hyp_ex])                
                    if verbose: print 'consistency check: (BK & T & H): %s' % consistent
                    
        return result

class DrtGlueReadingCommand(ReadingCommand):
    def __init__(self, semtype_file=None, remove_duplicates=False,
                 depparser=None):
        """
        :param semtype_file: name of file where grammar can be loaded
        :param remove_duplicates: should duplicates be removed?
        :param depparser: the dependency parser
        """
        if semtype_file is None:
            semtype_file = 'drt_glue.semtype'
        self._glue = DrtGlue(semtype_file=semtype_file,
                             remove_duplicates=remove_duplicates,
                             depparser=depparser)

    def parse_to_readings(self, sentence):
        """:see: ReadingCommand.parse_to_readings()"""
        return self._glue.parse_to_meaning(sentence)

    def process_thread(self, sentence_readings):
        """:see: ReadingCommand.process_thread()"""
        try:
            return [self.combine_readings(sentence_readings)]
        except AnaphoraResolutionException:
            return []

    def combine_readings(self, readings):
        """:see: ReadingCommand.combine_readings()"""
        thread_reading = reduce(add, readings)
        return resolve_anaphora(thread_reading.simplify())
    
    def to_fol(self, expression):
        """:see: ReadingCommand.to_fol()"""
        return expression.fol()

 def __init__(self, semtype_file=None, remove_duplicates=False, depparser=None):
     """
     :param semtype_file: name of file where grammar can be loaded
     :param remove_duplicates: should duplicates be removed?
     :param depparser: the dependency parser
     """
     if semtype_file is None:
         semtype_file = "drt_glue.semtype"
     self._glue = DrtGlue(semtype_file=semtype_file, remove_duplicates=remove_duplicates, depparser=depparser)

    def _init_glue(self):
        tagger = RegexpTagger(
            [('^(David|Mary|John)$', 'NNP'),
             ('^(walks|sees|eats|chases|believes|gives|sleeps|chases|persuades|tries|seems|leaves)$', '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)
        self._glue = DrtGlue(depparser=depparser, remove_duplicates=False)

class DrtGlueDemo(object):
    def __init__(self, examples):
        # Set up the main window.
        self._top = Tk()
        self._top.title('DRT Glue Demo')

        # Set up key bindings.
        self._init_bindings()

        # Initialize the fonts.self._error = None
        self._init_fonts(self._top)

        self._examples = examples
        self._readingCache = [None for example in examples]

        # The user can hide the grammar.
        self._show_grammar = IntVar(self._top)
        self._show_grammar.set(1)

        # Set the data to None
        self._curExample = -1
        self._readings = []
        self._drs = None
        self._drsWidget = None
        self._error = None

        self._init_glue()

        # Create the basic frames.
        self._init_menubar(self._top)
        self._init_buttons(self._top)
        self._init_exampleListbox(self._top)
        self._init_readingListbox(self._top)
        self._init_canvas(self._top)

        # Resize callback
        self._canvas.bind('<Configure>', self._configure)

    #########################################
    ##  Initialization Helpers
    #########################################

    def _init_glue(self):
        tagger = RegexpTagger(
            [('^(David|Mary|John)$', 'NNP'),
             ('^(walks|sees|eats|chases|believes|gives|sleeps|chases|persuades|tries|seems|leaves)$', '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)
        self._glue = DrtGlue(depparser=depparser, remove_duplicates=False)

    def _init_fonts(self, root):
        # See: <http://www.astro.washington.edu/owen/ROTKFolklore.html>
        self._sysfont = Font(font=Button()["font"])
        root.option_add("*Font", self._sysfont)

        # TWhat's our font size (default=same as sysfont)
        self._size = IntVar(root)
        self._size.set(self._sysfont.cget('size'))

        self._boldfont = Font(family='helvetica', weight='bold',
                                    size=self._size.get())
        self._font = Font(family='helvetica',
                                    size=self._size.get())
        if self._size.get() < 0: big = self._size.get()-2
        else: big = self._size.get()+2
        self._bigfont = Font(family='helvetica', weight='bold',
                                    size=big)

    def _init_exampleListbox(self, parent):
        self._exampleFrame = listframe = Frame(parent)
        self._exampleFrame.pack(fill='both', side='left', padx=2)
        self._exampleList_label = Label(self._exampleFrame, font=self._boldfont,
                                     text='Examples')
        self._exampleList_label.pack()
        self._exampleList = Listbox(self._exampleFrame, selectmode='single',
                                 relief='groove', background='white',
                                 foreground='#909090', font=self._font,
                                 selectforeground='#004040',
                                 selectbackground='#c0f0c0')

        self._exampleList.pack(side='right', fill='both', expand=1)

        for example in self._examples:
            self._exampleList.insert('end', ('  %s' % example))
        self._exampleList.config(height=min(len(self._examples), 25), width=40)

        # Add a scrollbar if there are more than 25 examples.
        if len(self._examples) > 25:
            listscroll = Scrollbar(self._exampleFrame,
                                   orient='vertical')
            self._exampleList.config(yscrollcommand = listscroll.set)
            listscroll.config(command=self._exampleList.yview)
            listscroll.pack(side='left', fill='y')
#.........这里部分代码省略.........

def demo_inference_tagger(verbose=False):
    tagger = RTEInferenceTagger()
    
    text = 'John see a car'
    print 'Text: ', text
    hyp = 'John watch an auto'
    print 'Hyp:  ', hyp

#    text_ex = LogicParser().parse('exists e x y.(david(x) & own(e)  & subj(e,x) & obj(e,y) & car(y))')
#    hyp_ex  = LogicParser().parse('exists e x y.(david(x) & have(e) & subj(e,x) & obj(e,y) & auto(y))')

    glueclass = DrtGlue(verbose=verbose)
    text_drs_list = glueclass.parse_to_meaning(text)
    if text_drs_list:
        text_ex = text_drs_list[0].simplify().toFol()
    else:
        print 'ERROR: No readings were be generated for the Text'
    
    hyp_drs_list = glueclass.parse_to_meaning(hyp)
    if hyp_drs_list:
        hyp_ex = hyp_drs_list[0].simplify().toFol()
    else:
        print 'ERROR: No readings were be generated for the Hypothesis'

    print 'Text: ', text_ex
    print 'Hyp:  ', hyp_ex
    print ''

    #1. proof T -> H
    #2. proof (BK & T) -> H
    #3. proof :(BK & T)
    #4. proof :(BK & T & H)
    #5. satisfy BK & T
    #6. satisfy BK & T & H
        
    result = inference.Prover9().prove(hyp_ex, [text_ex])
    print 'prove: T -> H: %s' % result
    if result:
        print 'Logical entailment\n'
    else:
        print 'No logical entailment\n'

    bk = tagger._generate_BK(text, hyp, verbose)
    bk_exs = [bk_pair[0] for bk_pair in bk]
    
    print 'Generated Background Knowledge:'
    for bk_ex in bk_exs:
        print bk_ex
    print ''
        
    result = inference.Prover9().prove(hyp_ex, [text_ex]+bk_exs)
    print 'prove: (T & BK) -> H: %s' % result
    if result:
        print 'Logical entailment\n'
    else:
        print 'No logical entailment\n'

    # Check if the background knowledge axioms are inconsistent
    result = inference.Prover9().prove(assumptions=bk_exs+[text_ex]).prove()
    print 'prove: (BK & T): %s' % result
    if result:
        print 'Inconsistency -> Entailment unknown\n'
    else:
        print 'No inconsistency\n'

    result = inference.Prover9().prove(assumptions=bk_exs+[text_ex, hyp_ex])
    print 'prove: (BK & T & H): %s' % result
    if result:
        print 'Inconsistency -> Entailment unknown\n'
    else:
        print 'No inconsistency\n'

    result = inference.Mace().build_model(assumptions=bk_exs+[text_ex])
    print 'satisfy: (BK & T): %s' % result
    if result:
        print 'No inconsistency\n'
    else:
        print 'Inconsistency -> Entailment unknown\n'

    result = inference.Mace().build_model(assumptions=bk_exs+[text_ex, hyp_ex]).build_model()
    print 'satisfy: (BK & T & H): %s' % result
    if result:
        print 'No inconsistency\n'
    else:
        print 'Inconsistency -> Entailment unknown\n'