def __init__(self, discourse_id=None):
"""
This class is used to parse the Prolog DRS output from Boxer into a
hierarchy of python objects.
"""
DrtParser.__init__(self)
self.discourse_id = discourse_id
self.sentence_id_offset = None
self.quote_chars = [("'", "'", "\\", False)]
def __init__(self, discourse_id=None):
"""
This class is used to parse the Prolog DRS output from Boxer into a
hierarchy of python objects.
"""
DrtParser.__init__(self)
self.discourse_id = discourse_id
self.sentence_id_offset = None
self.quote_chars = [("'", "'", "\\", False)]
def drs_matcher(s, p, QA_services, debug="no"):
res = []
parser = load_parser(p, trace=0, logic_parser=DrtParser())
#NotImlementedError
try:
for tree in parser.parse(s.split()):
if (
debug == "yes"
): #forwarding output to do further testing when developing new grammar rules
res.append(tree)
elif (debug == "no"):
res.append(str(tree.label()['SEM'].simplify()))
#if we have a failure in the parser tree, return False or rethrow exception
except:
print('exception occurred')
if (
debug == "yes"
): #forwarding output to do further testing when developing new grammar rules
raise
elif (debug == "no"):
return False
if (
debug == "yes"
): #forwarding output to do further testing when developing new grammar rules
return res
elif (debug == "no"):
if res != []:
#return the DRS obtained from the first tree of the forest, if it exist
#TODO: look for a tree with same structure as published by GNLP (provided it exist and it makes sense)
DRS = res[0]
QA_services.write_to_KB(DRS, TAG_DRS)
return True
else:
return False
def __init__(self, discourse_id=None):
DrtParser.__init__(self)
self.discourse_id = discourse_id
def parse(self, data, signature=None):
self._label_counter = Counter(-1)
return DrtParser.parse(self, data, signature)
def __init__(self, discourse_id=None):
DrtParser.__init__(self)
self.discourse_id = discourse_id
def parse(self, data, signature=None):
return DrtParser.parse(self, data, signature)
def parse(self, data, signature=None):
self._label_counter = Counter(-1)
return DrtParser.parse(self, data, signature)
def parse(self, data, signature=None):
return DrtParser.parse(self, data, signature)
print(dexpr(s))
# The fol() method converts DRSs into FOL formulae.
print(dexpr(r'([x],[man(x), walks(x)])').fol())
print(dexpr(r'([],[(([x],[man(x)]) -> ([],[walks(x)]))])').fol())
# In order to visualize a DRS, the pretty_format() method can be used.
print(drs3.pretty_format())
# PARSE TO SEMANTICS
# DRSs can be used for building compositional semantics in a feature based grammar. To specify that we want to use DRSs, the appropriate logic parser needs be passed as a parameter to load_earley()
from nltk.parse import load_parser
from nltk.sem.drt import DrtParser
parser = load_parser('grammars/book_grammars/drt.fcfg',
trace=0,
logic_parser=DrtParser())
for tree in parser.parse('a dog barks'.split()):
print(tree.label()['SEM'].simplify())
# Alternatively, a FeatStructReader can be passed with the logic_parser set on it
from nltk.featstruct import FeatStructReader
from nltk.grammar import FeatStructNonterminal
parser = load_parser('grammars/book_grammars/drt.fcfg',
trace=0,
fstruct_reader=FeatStructReader(
fdict_class=FeatStructNonterminal,
logic_parser=DrtParser()))
for tree in parser.parse('every girl chases a dog'.split()):
print(tree.label()['SEM'].simplify().normalize())