def get_results(testing, m):
for pair in testing:
gold_paras=[]
for p in pair.paraphrases:
gold_paras.append(p)
if len(gold_paras)>2:
subs=random.sample(gold_paras,3)
else:
errcount+=1
print "List too short error."
continue
base=[]
for t in totals:
if Paraphrase(t[0]) not in subs:
base.append(Paraphrase(t[0]))
if len(base)==m: break
# a list of all paraphrases, to be ordered by score for this compound
results=[]
for p in probs.keys():
x=Paraphrase(p.strip())
x.score=0.0
#the seed paraphrases are not allowed in predictions
if not x in subs: results.append(x)
for p in results:
for s in subs:
try:
p.score+=probs[p.name][s.name]
nonerrcount+=1
#print "done"
except KeyError:
errcount+=1
#print errcount
#print "Key Error"
results.sort(key= lambda para: para.score, reverse=True)
score=0.0
basescore=0.0
for b in base[0:m]:
if b in gold_paras:basescore+=1.0
for r in results[0:m]:
if r in gold_paras:score+=1.0
total+=(score/float(m))
basetotal+=(basescore/float(m))
acc=total/len(testing)
print "predictions:"
print total/len(testing)
print
baseacc=basetotal/len(testing)
print "baseline:"
print basetotal/len(testing)
print errcount
print nonerrcount
results=[acc,baseacc]
return results
def get_results(training,testing, m):
w=Web1TSearch("/media/Iomega HDD/web1T/clean/")
#w=Web1TSearch("/media/usb0/web1T/clean/")
print "bulding probability table..."
priors=make_priors(training)
probs=make_prob_table(training, priors)
count=0
print "done."
total=0.0
basetotal=0.0
errcount=0
nonerrcount=0
#baseline of most frequent overall paraphrases
totals=sorted(priors.items(), key=lambda x: x[1], reverse=True)
for pair in testing:
count+=1
print count
print "\n\n*************************************\n\n"
gold_paras=[]
for p in pair.paraphrases:
gold_paras.append(p)
subs=[]
print pair.n2 + " " + pair.n1
r= w.getNgrams(pair.n2,pair.n1)
r= w.reducePats(r,pair.n2,pair.n1)
sortedResults=sorted(r.iteritems(), key=lambda (k,v): (v,k),reverse=True)
for s in sortedResults:
p=Paraphrase(s[0].replace('_',' ') )
if p.name in priors.keys():
subs.append(p)
print p.name
if "be "+ p.name in priors.keys():
subs.append(Paraphrase("be "+p.name))
print p.name
base=[]
for t in totals:
if Paraphrase(t[0]) not in subs:
base.append(Paraphrase(t[0]))
if len(base)==m: break
# a list of all paraphrases, to be ordered by score for this compound
results=[]
for p in probs.keys():
x=Paraphrase(p.strip())
x.score=0.0
#the seed paraphrases are not allowed in predictions
if not x in subs: results.append(x)
for p in results:
for s in subs:
try:
p.score+=probs[p.name][s.name]
nonerrcount+=1
#print "done"
except KeyError:
errcount+=1
#print errcount
#print "Key Error"
results.sort(key= lambda para: para.score, reverse=True)
if len(subs)==0: results=copy.copy(base)
print
print "Gold:"
for g in gold_paras: print g.name
print
print "Seeds"
for s in subs: print s.name
print
print "Predictions: "
for p in results[0:m]:print p.name
print
print "Baseline:"
for b in base: print b.name
print
score=0.0
basescore=0.0
for b in base[0:m]:
if b in gold_paras:basescore+=1.0
for r in results[0:m]:
if r in gold_paras:score+=1.0
total+=(score/float(m))
basetotal+=(basescore/float(m))
acc=total/len(testing)
print "predictions:"
print total/len(testing)
print
baseacc=basetotal/len(testing)
print "baseline:"
print basetotal/len(testing)
print errcount
print nonerrcount
results=[acc,baseacc]
return results
inp=raw_input()
if inp in priors:
seeds.append(Paraphrase(inp))
else:
print "not found"
print "working..."
for pair in all_pairs:
paras=[]
for p in pair.paraphrases:
if p.freq < n : continue
paras.append(p)
results=[]
for p in probs.keys():
x=Paraphrase(p.strip())
x.score=0.0
#the seed paraphrases are not allowed in predictions
if not x in seeds: results.append(x)
for p in results:
for s in seeds:
try:
p.score+=probs[p.name][s.name]
#print "done"
except KeyError:
pass
print "Key Error"
results.sort(key= lambda para: para.score, reverse=True)
for r in results[0:10]:
def get_results(training,testing, m):
print "bulding probability table..."
priors=make_priors_freq(training)
probs=make_prob_table(training, priors)
print "done."
total=0.0
basetotal=0.0
rand_basetotal=0.0
errcount=0
nonerrcount=0
#baseline of most frequent overall paraphrases
totals=sorted(priors.items(), key=lambda x: x[1], reverse=True)
for pair in testing:
gold_paras=[]
for p in pair.paraphrases:
gold_paras.append(p)
if len(gold_paras)>2:
subs=random.sample(gold_paras,3)
else:
errcount+=1
print "List too short error."
continue
base=[]
for t in totals:
if Paraphrase(t[0]) not in subs:
base.append(Paraphrase(t[0]))
if len(base)==m: break
rand_base=[]
i=0
while(i<3):
p=Paraphrase(random.choice(priors.keys()))
if p not in subs:
rand_base.append(p)
i+=1
for t in totals:
if Paraphrase(t[0]) not in subs:
base.append(Paraphrase(t[0]))
if len(base)==m: break
# a list of all paraphrases, to be ordered by score for this compound
results=[]
for p in probs.keys():
x=Paraphrase(p.strip())
x.score=0.0
#the seed paraphrases are not allowed in predictions
if not x in subs: results.append(x)
for p in results:
p.score=priors[p.name]
for s in subs:
try:
p.score=p.score*probs[p.name][s.name]
nonerrcount+=1
#print "done"
except KeyError:
errcount+=1
#print errcount
#print "Key Error"
results.sort(key= lambda para: para.score, reverse=True)
score=0.0
basescore=0.0
rand_basescore=0.0
for p in rand_base[0:m]:
if p in gold_paras:rand_basescore+=1.0
for b in base[0:m]:
if b in gold_paras:basescore+=1.0
for r in results[0:m]:
if r in gold_paras:score+=1.0
total+=(score/float(m))
basetotal+=(basescore/float(m))
rand_basetotal+=(rand_basescore/float(m))
acc=total/len(testing)
print "predictions:"
print total/len(testing)
print
baseacc=basetotal/len(testing)
print "most frequent baseline:"
print basetotal/len(testing)
rand_baseacc=rand_basetotal/len(testing)
print "random baseline:"
print rand_basetotal/len(testing)
print errcount
print nonerrcount
results=[acc,baseacc, rand_baseacc]
return results