def __init__(self):
print("Initializing INFERNO NLG Engine...")
self.pp = pprint.PrettyPrinter(indent=4)
self.realise = Realiser(host='nlg.kutlak.info', port=40000)
self.ontology_base_url = "http://www.semanticweb.org/raneeshgomez/ontologies/2020/fyp-solar-system#"
self.rdf_base_url = "http://www.w3.org/1999/02/22-rdf-syntax-ns#"
self.rdfs_base_url = "http://www.w3.org/2000/01/rdf-schema#"
self.owl_base_url = "http://www.w3.org/2002/07/owl#"
self.disregarded_types = ['DatatypeProperty', 'ObjectProperty', 'InverseObjectProperty', 'NamedIndividual',
'AnonymousIndividual', 'Class', 'TransitiveProperty', 'FunctionalProperty',
'InverseFunctionalProperty', 'SymmetricProperty', 'Restriction']
def translate(request):
"""Read a given FOL formula as jason data and return it as text. """
response_data = {}
formula = request.POST['formula'].strip()
response_data['formula'] = formula
simplifications = [
x.strip() for x in request.POST.get('simplifications', '').split('|')
]
try:
realise = Realiser(host='roman.kutlak.info')
if formula:
template_instances = TemplateModel.objects.all()
templates = {}
errors = []
for t in template_instances:
name = t.name
try:
template = eval(t.content)
templates[name] = template
except Exception as e:
errors.append(
('danger', str(e))) # use bootstrap terminology...
lex = Lexicaliser(templates=templates)
response_data['text'] = realise(lex(formula_to_rst(expr(formula))))
response_data['status'] = 'success'
response_data['messages'] = json.dumps(errors)
else:
response_data[
'text'] = "Enter a formula first. E.g., 'happy(roman)'"
response_data['status'] = 'default'
except nltk.sem.logic.LogicalExpressionException as e:
response_data['text'] = str(e)
response_data['status'] = 'error'
except Exception as e:
logger.exception(e)
return JsonResponse(response_data)
from nlglib.realisation.simplenlg.realisation import Realiser
from nlglib.microplanning import *
realise_en = Realiser(host='nlg.kutlak.info', port=40000)
realise_es = Realiser(host='nlg.kutlak.info', port=40001)
def main():
p = Clause(Mara, perseguir, un mono)
p['TENSE'] = 'PAST'
# expected = 'Mara persigue un mono'
print(realise_es(p))
p = Clause(NP(la, rpida, corredora), VP(perseguir), NP(un, mono))
subject = NP(la, corredora)
objekt = NP(un, mono)
verb = VP(perseguir)
subject.premodifiers.append(rpida)
p.subject = subject
p.predicate = verb
p.object = objekt
# expected = 'La rpida corredora persigue un mono.'
print(realise_es(p))
p = Clause(NP('this', 'example'), VP('show', 'how cool simplenlg is'))
# expected = This example shows how cool simplenlg is.
print(realise_en(p))
if __name__ == '__main__':
main()
#Build Text Model using Makovify
text_model = markovify.NewlineText(input_text.headline_text, state_size = 2)
#Generate Random Headlines
# Print ten randomly-generated sentences using the built model
for i in range(10):
print(text_model.make_sentence())
#SimpleNLG
#Load the library
import logging
from nlglib.realisation.simplenlg.realisation import Realiser
from nlglib.microplanning import *
realise = Realiser(host='nlg.kutlak.info')
#Tense
def tense():
c = Clause('Harry', 'bought', 'these off amazon')
c['TENSE'] = 'PAST'
print(realise(c))
c['TENSE'] = 'FUTURE'
print(realise(c))
#Negation
def negation():
c = Clause('Harry', 'bought', 'these off amazon')
c['NEGATED'] = 'true'
print(realise(c))
from nlglib.realisation.simplenlg.realisation import Realiser
from nlglib.microplanning import *
realise_en = Realiser(host='roman.kutlak.info', port=40000)
p = Clause(NP('this', 'example'), VP('show', 'how cool simplenlg is'))
print(realise_en(p))
def __init__(self):
self.realise = Realiser(host='nlg.kutlak.info')
self.ngram = n_gram(3, .06, logging=True)
self.ngram.manual_interpolation([.6, .3, .1])
self.ngram.load_n_gram()
def run():
realise = Realiser(host='nlg.kutlak.info')
lex = Lexicaliser(
templates={
'x':
String('X'),
'arthur':
Male('Arthur'),
'shrubbery':
Clause(Var(0),
VP('find', NP('a', 'shrubbery'), features=[TENSE.future])),
'knight':
Clause(Var(0), VP('is', NP('a', 'knight'))),
'say_ni':
Clause(Var(0), VP('say', Interjection('"Ni!"'))),
})
print(realise(lex(formula_to_rst(expr(r'x')))))
print(realise(lex(formula_to_rst(expr(r'-x')))))
print(realise(lex(formula_to_rst(expr(r'x = 5')))))
print(realise(lex(formula_to_rst(expr(r'x != 5')))))
print(realise(lex(formula_to_rst(expr(r'knight(arthur)')))))
print(realise(lex(formula_to_rst(expr(r'-knight(arthur)')))))
print(realise(lex(formula_to_rst(expr(r'say_ni(arthur)')))))
print(realise(lex(formula_to_rst(expr(r'-say_ni(arthur)')))))
print(realise(lex(formula_to_rst(expr(r'shrubbery(arthur)')))))
print(realise(lex(formula_to_rst(expr(r'-shrubbery(arthur)')))))
print(
realise(lex(formula_to_rst(expr(r'knight(arthur) & say_ni(arthur)')))))
print(
realise(lex(formula_to_rst(expr(r'say_ni(arthur) | knight(arthur)')))))
print(
realise(lex(formula_to_rst(
expr(r'say_ni(arthur) -> knight(arthur)')))))
print(
realise(lex(formula_to_rst(
expr(r'knight(arthur) <-> say_ni(arthur)')))))
print(
realise(lex(formula_to_rst(
expr(r'say_ni(arthur) & -knight(arthur)')))))
print(
realise(lex(formula_to_rst(
expr(r'say_ni(arthur) | -knight(arthur)')))))
print(
realise(lex(formula_to_rst(
expr(r'say_ni(arthur) -> -knight(arthur)')))))
print(
realise(
lex(formula_to_rst(expr(r'-knight(arthur) <-> say_ni(arthur)')))))
print(
realise(
lex(formula_to_rst(expr(r'-knight(arthur) <-> -say_ni(arthur)')))))
print(
realise(
lex(formula_to_rst(
expr(r'-(knight(arthur) <-> say_ni(arthur))')))))
print(
realise(
lex(
formula_to_rst(
expr(r'say_ni(arthur) & knight(arthur) & shrubbery(arthur)'
)))))
print(
realise(
lex(
formula_to_rst(
expr(r'say_ni(arthur) | knight(arthur) | shrubbery(arthur)'
)))))