def demo():
from nltk.sem import cooper_storage as cs
sentence = "every girl chases a dog"
#sentence = "a man gives a bone to every dog"
print()
print("Analyis of sentence '%s'" % sentence)
print("=" * 50)
trees = cs.parse_with_bindops(sentence, trace=0)
for tree in trees:
semrep = cs.CooperStore(tree.label()['SEM'])
print()
print("Binding operators:")
print("-" * 15)
for s in semrep.store:
print(s)
print()
print("Core:")
print("-" * 15)
print(semrep.core)
print()
print("S-Retrieval:")
print("-" * 15)
semrep.s_retrieve(trace=True)
print("Readings:")
print("-" * 15)
for i, reading in enumerate(semrep.readings):
print("%s: %s" % (i+1, reading))
def demo():
from nltk.sem import cooper_storage as cs
sentence = "every girl chases a dog"
#sentence = "a man gives a bone to every dog"
print()
print("Analyis of sentence '%s'" % sentence)
print("=" * 50)
trees = cs.parse_with_bindops(sentence, trace=0)
for tree in trees:
semrep = cs.CooperStore(tree.node['SEM'])
print()
print("Binding operators:")
print("-" * 15)
for s in semrep.store:
print(s)
print()
print("Core:")
print("-" * 15)
print(semrep.core)
print()
print("S-Retrieval:")
print("-" * 15)
semrep.s_retrieve(trace=True)
print("Readings:")
print("-" * 15)
for i, reading in enumerate(semrep.readings):
print("%s: %s" % (i + 1, reading))
def demo():
from nltk.sem import cooper_storage as cs
sentence = "every girl chases a dog"
# sentence = "a man gives a bone to every dog"
print
print "Analyis of sentence '%s'" % sentence
print "=" * 50
trees = cs.parse_with_bindops(sentence, trace=0)
for tree in trees:
semrep = cs.CooperStore(tree.node["SEM"])
print
print "Binding operators:"
print "-" * 15
for s in semrep.store:
print s
print
print "Core:"
print "-" * 15
print semrep.core
print
print "S-Retrieval:"
print "-" * 15
semrep.s_retrieve(trace=True)
print "Readings:"
print "-" * 15
for i, reading in enumerate(semrep.readings):
print "%s: %s" % (i + 1, reading)
print semantic_representation.s_retrieve,'k' semantic_representation.s_retrieve() for reading in semantic_representation.readings: print 'Reading %s'%reading print 'Simplified Reading %s'%reading.simplify() print 'Predicates: ', reading.predicates() print 'Variables: ',reading.variables() hpi = "33_year_old man with coronary_artery_disease complicated_by coronary_artery_bypass_graft in 2010" #hpi = '33_year_old man' #hpi = "stroke and coronary_artery_disease in 2010" #hpi = "33_year_old man with coronary_artery_disease and stroke in 2010" #hpi = "coronary_artery_disease complicated_by coronary_artery_bypass_graft" #parser = nltk.parse.FeatureEarleyChartParser(grammar) #trees = cs.parse_with_bindops(hpi, grammar=r'./with.fcfg') trees = cs.parse_with_bindops(hpi, grammar=r'./many-quantified-nps.fcfg') #trees = [tree for tree in parser.parse(hpi)] if len(trees) == 1: trees[0].draw() parse_cooper_storage(trees[0]) else: print '%d trees. Have to choose'%len(trees) print 'No choice function defined' for tree in trees: tree.draw() parse_cooper_storage(tree)
print(expr1)
expr2 = expr1.alpha_convert(nltk.sem.Variable('z'))
print(expr2)
expr1 == expr2
expr3 = read_expr('\P.(exists x.P(x))(\y.see(y, x))')
print(expr3)
print(expr3.simplify())
##量词歧义
from nltk.sem import cooper_storage as cs
sentence = 'every girl chases a dog'
trees = cs.parse_with_bindops(sentence,
grammar='grammars/book_grammars/storage.fcfg')
semrep = trees[0].label()['SEM']
cs_semrep = cs.CooperStore(semrep)
print(cs_semrep.core)
for bo in cs_semrep.store:
print(bo)
cs_semrep.s_retrieve(trace=True)
for reading in cs_semrep.readings:
print(reading)
#段落语义理解
read_dexpr = nltk.sem.DrtExpression.fromstring
drs1 = read_dexpr('([x, y], [angus(x), dog(y), own(x, y)])')
print semantic_representation.s_retrieve, 'k'
semantic_representation.s_retrieve()
for reading in semantic_representation.readings:
print 'Reading %s' % reading
print 'Simplified Reading %s' % reading.simplify()
print 'Predicates: ', reading.predicates()
print 'Variables: ', reading.variables()
hpi = "33_year_old man with coronary_artery_disease complicated_by coronary_artery_bypass_graft in 2010"
#hpi = '33_year_old man'
#hpi = "stroke and coronary_artery_disease in 2010"
#hpi = "33_year_old man with coronary_artery_disease and stroke in 2010"
#hpi = "coronary_artery_disease complicated_by coronary_artery_bypass_graft"
#parser = nltk.parse.FeatureEarleyChartParser(grammar)
#trees = cs.parse_with_bindops(hpi, grammar=r'./with.fcfg')
trees = cs.parse_with_bindops(hpi, grammar=r'./many-quantified-nps.fcfg')
#trees = [tree for tree in parser.parse(hpi)]
if len(trees) == 1:
trees[0].draw()
parse_cooper_storage(trees[0])
else:
print '%d trees. Have to choose' % len(trees)
print 'No choice function defined'
for tree in trees:
tree.draw()
parse_cooper_storage(tree)
from nltk.sem import cooper_storage as cs from nltk.draw.util import CanvasFrame from nltk.draw import TreeWidget sentence = 'a girl chases a dog' trees = cs.parse_with_bindops(sentence, grammar=r'./storage.fcfg') trees[0].draw()
