def discoverObject(object):
print(Mag + "Building concept to search KB for" + st, object.lemma_)
features = languageTools.extractFeatures(object)
facts = [["inst", "?x", object.lemma_]]
for f in features:
type = kb.whatAmI(f.lemma_)
facts.append([type, "?x", f.lemma_])
print(Mag + "Looking for an ?x that matches:" + st)
for f in facts:
print(" ", f)
bindings = kb.betterAsk(facts)
if len(bindings) != 1:
if object.text[-1] == "s":
print(Mag + "Found reference in KB:")
elements = [a for a in map(lambda x: x["?x"], bindings)]
recentMemory.addElements(object.lemma_, elements)
return elements
else:
print(
Mag +
"We have a problem with too many objects matching in the KB" +
st)
elif bindings == False:
print(
Mag +
"We have a problem because nothing matches these facts in the KB" +
st)
else:
print(Mag + "Found reference in KB:" + st, bindings[0]["?x"])
recentMemory.addElements(object.lemma_, [bindings[0]["?x"]])
return [bindings[0]["?x"]]
def discoverQuantifiedObjects(object):
count_number = utilities.countNumber(False,object)
reference = languageTools.trackReference(object)
print(Cyn+"Building concept to search KB for"+st,object.lemma_, "'"+reference.lemma_+"'")
features = languageTools.extractFeatures(object)
facts = [["inst","?x",reference.lemma_]]
for f in features:
type = kb.whatAmI(f.lemma_)
facts.append([type,"?x",f.lemma_])
print(rd+"Looking for an ?x that matches:"+st)
for f in facts:
print(" ",f)
bindings=kb.betterAsk(facts)
if len(bindings) < count_number:
print(Cyn+"We have a problem with too few objects matching in the KB"+st)
elif bindings == False:
print(Cyn+"We have a problem because nothing matches these facts in the KB"+st)
else:
print(Cyn+"Found references in KB:")
print(Cyn+"Selecting a subset from",len(bindings),"elements")
candidates = [a for a in map(lambda x: x["?x"], bindings)]
print(longTermMemory)
remaining = longTermMemory.getElementAndStatus(reference.lemma_, "remaining")
if remaining:
candidates = [a for a in filter(lambda x: x in remaining, candidates)]
print(Cyn+"Filtering off of last statement")
names = candidates[0:count_number]
others = candidates[count_number:]
print(Cyn+"Selected"+st, names)
recentMemory.addElements(reference.lemma_, names)
recentMemory.addElementAndStatus(reference.lemma_, others, "remaining")
return names
def discoverObject(object):
print(Mag+"Building concept to search KB for"+st,object.lemma_)
features = languageTools.extractFeatures(object)
facts = [["inst","?x",object.lemma_]]
for f in features:
type = kb.whatAmI(f.lemma_)
facts.append([type,"?x",f.lemma_])
print(Mag+"Looking for an ?x that matches:"+st)
for f in facts:
print(" ",f)
bindings=kb.betterAsk(facts)
if len(bindings) != 1:
if object.text[-1] == "s":
print(Mag+"Found reference in KB:")
elements = [a for a in map(lambda x: x["?x"], bindings)]
recentMemory.addElements(object.lemma_,elements)
return elements
else:
print(Mag+"We have a problem with too many objects matching in the KB"+st)
elif bindings == False:
print(Mag+"We have a problem because nothing matches these facts in the KB"+st)
else:
print(Mag+"Found reference in KB:"+st,bindings[0]["?x"])
recentMemory.addElements(object.lemma_,[bindings[0]["?x"]])
return [bindings[0]["?x"]]
def discoverQuantifiedObjects(object):
count_number = utilities.countNumber(False,object)
reference = languageTools.trackReference(object)
print(Cyn+"Building concept to search KB for"+st,object.lemma_, "'"+reference.lemma_+"'")
features = languageTools.extractFeatures(object)
facts = [["inst","?x",reference.lemma_]]
for f in features:
type = kb.whatAmI(f.lemma_)
facts.append([type,"?x",f.lemma_])
print(rd+"Looking for an ?x that matches:"+st)
for f in facts:
print(" ",f)
bindings=kb.betterAsk(facts)
if len(bindings) < count_number:
print(Cyn+"We have a problem with too few objects matching in the KB"+st)
elif bindings == False:
print(Cyn+"We have a problem because nothing matches these facts in the KB"+st)
else:
print(Cyn+"Found references in KB:")
print(Cyn+"Selecting a subset from",len(bindings),"elements")
candidates = [a for a in map(lambda x: x["?x"], bindings)]
print(longTermMemory)
remaining = longTermMemory.getElementAndStatus(reference.lemma_, "remaining")
if remaining:
candidates = [a for a in filter(lambda x: x in remaining, candidates)]
print(Cyn+"Filtering off of last statement")
names = candidates[0:count_number]
others = candidates[count_number:]
print(Cyn+"Selected"+st, names)
recentMemory.addElements(reference.lemma_, names)
recentMemory.addElementAndStatus(reference.lemma_, others, "remaining")
return names
def findAndAssertFeaturesFOPC(object, names):
print(Ylw + "Checking features to modify" + st, names)
features = languageTools.extractFeatures(object)
for feature in features:
print(Ylw + "Found" + st, feature)
feature_type = kb.whatAmI(feature.lemma_)
for name in names:
kb.assertFromStatement([feature_type, name, feature.lemma_])
statements.append([feature_type, name, feature.lemma_])
def findAndAssertFeaturesFOPC(object,names):
print(Ylw+"Checking features to modify"+st, names)
features = languageTools.extractFeatures(object)
for feature in features:
print(Ylw+"Found"+st,feature)
feature_type = kb.whatAmI(feature.lemma_)
for name in names:
kb.assertFromStatement([feature_type, name, feature.lemma_])
statements.append([feature_type, name, feature.lemma_])