def tryToFindRela(jobid, filename, dataInputPath, ptnOutputPath, model, table):
content = projizz.combinedFileReader(os.path.join(dataInputPath, filename))
print "Worker %d : Read %s into filter" % (jobid, filename)
count = 0
dealL = 0
patternEx = {}
for articleName in content:
pattern = []
article = projizz.articleSimpleSentenceFileter(content[articleName])
lineCount = 0
for line in article:
dealL += 1
tokens = projizz._posTagger.tag(line)
patternExtracted = projizz.naiveExtractPatterns(tokens, model)
if len(patternExtracted) > 0:
pattern.append((lineCount, patternExtracted))
if dealL % 10000 == 0:
print "Worker %d deal with %d lines." % (jobid, dealL)
lineCount += 1
patternEx[articleName] = pattern
count += 1
if count % 100 == 0:
print "Worker %d deal with %d files" % (jobid, count)
gc.collect()
projizz.combinedFileWriter(patternEx, os.path.join(ptnOutputPath,
filename))
print "Worker %d : Write results out to %s." % (jobid, filename)
def tryToFindRela(jobid, filename, dataInputPath, ptnOutputPath, model, table):
content = projizz.combinedFileReader(os.path.join(dataInputPath,filename))
print "Worker %d : Read %s into filter" % (jobid,filename)
count = 0
dealL = 0
patternEx = {}
for articleName in content:
pattern = []
article = projizz.articleSimpleSentenceFileter(content[articleName])
lineCount = 0
for line in article:
dealL += 1
tokens = projizz._posTagger.tag(line)
patternExtracted = projizz.naiveExtractPatterns(tokens,model)
if len(patternExtracted) > 0:
pattern.append((lineCount,patternExtracted))
if dealL % 10000 == 0:
print "Worker %d deal with %d lines." % (jobid,dealL)
lineCount += 1
patternEx[articleName] = pattern
count += 1
if count % 100 == 0:
print "Worker %d deal with %d files" % (jobid,count)
gc.collect()
projizz.combinedFileWriter(patternEx,os.path.join(ptnOutputPath,filename))
print "Worker %d : Write results out to %s." % (jobid,filename)
def tryToFindRela(jobid, filename, dataInputPath, resultOutPath, ptnOutputPath, model, tree):
content = projizz.combinedFileReader(os.path.join(dataInputPath,filename))
print "Worker %d : Read %s into filter" % (jobid,filename)
count = 0
dealL = 0
results = {}
patternEx = {}
for articleName in content:
result = {}
pattern = []
article = projizz.articleSimpleSentenceFileter(content[articleName])
for line in article:
tokens = projizz._posTagger.tag(line)
patternExtracted = projizz.naiveExtractPatterns(tokens,model)
for ptnId,start,to in patternExtracted:
dealL += 1
rels = tree[ptnId]["relations"]
if len(rels) < 2:
for r in rels:
if not r in result:
result[r] = 0
result[r] += 1
if not ptnId in pattern:
pattern.append(ptnId)
if dealL % 10000 == 0:
print "Worker %d deal with %d lines." % (jobid,dealL)
results[articleName] = result
patternEx[articleName] = pattern
count += 1
if count % 100 == 0:
print "Worker %d deal with %d files" % (jobid,count)
gc.collect()
projizz.combinedFileWriter(results,os.path.join(resultOutPath,filename))
projizz.combinedFileWriter(patternEx,os.path.join(ptnOutputPath,filename))
print "Worker %d : Write results out to %s." % (jobid,filename)
def testing(filename):
content = projizz.combinedFileReader(filename)
model, table = projizz.readPrefixTreeModel("./../prefix_tree_model/patternTree.json")
start_time = datetime.now()
for articleName in content:
print articleName
article = projizz.articleSimpleSentenceFileter(content[articleName])
for line in article:
tokens = projizz._posTagger.tag(line)
patternExtracted = projizz.naiveExtractPatterns(tokens,model)
if len(patternExtracted)>0:
print line.encode("utf-8")
for ptnId,start,to in patternExtracted:
print "\t[%d] %s" % (ptnId,table[ptnId]["pattern"])
print "\n----"
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds,diff.microseconds)
def testing(filename):
content = projizz.combinedFileReader(filename)
model, table = projizz.readPrefixTreeModel(
"./../prefix_tree_model/patternTree.json")
start_time = datetime.now()
for articleName in content:
print articleName
article = projizz.articleSimpleSentenceFileter(content[articleName])
for line in article:
tokens = projizz._posTagger.tag(line)
patternExtracted = projizz.naiveExtractPatterns(tokens, model)
if len(patternExtracted) > 0:
print line.encode("utf-8")
for ptnId, start, to in patternExtracted:
print "\t[%d] %s" % (ptnId, table[ptnId]["pattern"])
print "\n----"
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds, diff.microseconds)
def filterFunction(jobid,filename,inputPtnPath,model,table,partAns,st,domainRange,inputPath):
# read patterns in articles
contentPtnJson = json.load(open(os.path.join(inputPtnPath,filename),"r"))
# read articles
contentJson = json.load(open(os.path.join(inputPath,filename),"r"))
print "Worker %d : Read %s into filter" % (jobid,filename)
politicalPosition = ["Secretary","Premier","Mayor","Captain","Minister","Chief","Governor","General","Ambassadors","Member"]
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid":{"$in":queries}})
print "worker %d query=%d, result=%d" % (jobid,len(queries),itr.count())
count = 0
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
targetName = projizz.getNamedEntityTokens(ans["_id"]) # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
relaEx = []
for line in ptnEx: # line[0]: line number
lineText = article[line[0]]
named = False
for namedToken in targetName:
if namedToken in lineText:
named = True
break
if not named: # No target name in line text
continue # go to next line.
for ptn in line[1]: # line[1]: array of patterns
ptnId = "%d" % (ptn[0]) # ptn[0]: pattern ID, [1]: start, [2]: end
rfp = table[ptnId]["relations"]
# ignore non-used pattern
if not table[ptnId]["used"]:
continue
if "eval" in table[ptnId] and not table[ptnId]["eval"]:
continue
# never seen pattern
if not ptnId in st:
continue
# if only one relation
if len(rfp) < 2:
if "holdsPoliticalPosition" in rfp:
foundPosition = False
for position in politicalPosition:
if position in lineText and not "holdsPoliticalPosition" in relaEx:
relaEx.append("holdsPoliticalPosition")
break
if foundPosition:
continue
if st[ptnId][0][1]["support"] > 0 and not rfp[0] in relaEx:
relaEx.append(rfp[0])
# more than one relation
else:
if "holdsPoliticalPosition" in rfp:
foundPosition = False
for position in politicalPosition:
if position in lineText and not "holdsPoliticalPosition" in relaEx:
relaEx.append("holdsPoliticalPosition")
break
if foundPosition:
continue
# using the first as the answer
if st[ptnId][0][1]["support"] > 0 and not rfp[0] in relaEx:
relaEx.append(rfp[0])
# Remove impossible relations
toBeRemove = []
for attribute in relaEx:
# speical case, produced
if domainRange[attribute] == "":
continue
if not domainRange[attribute]["domain"] in types:
if not attribute in toBeRemove:
toBeRemove.append(attribute)
for attribute in toBeRemove:
relaEx.remove(attribute)
# Evaluation
for attribute in partAns:
postive = False
true = False
if attribute in relaEx:
postive = True
if attribute in relation:
true = True
if true:
if postive:
partAns[attribute]["tp"].append(ans["revid"])
else:
partAns[attribute]["fn"].append(ans["revid"])
else:
if postive:
partAns[attribute]["fp"].append(ans["revid"])
else:
partAns[attribute]["tn"].append(ans["revid"])
if count % 100 == 0:
print "worker #%d done %d." % (jobid,count)
return partAns
def mapper(jobid, filename, inputPath, inputPtnPath, table, st, partAns,
domainRange, confidence, vsmData):
# read articles and patterns
contentJson = projizz.jsonRead(os.path.join(inputPath, filename))
contentPtnJson = projizz.jsonRead(os.path.join(inputPtnPath, filename))
print "Worker %d : Read %s" % (jobid, filename)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid": {"$in": queries}})
print "worker %d query=%d, result=%d" % (jobid, len(queries), itr.count())
count = 0
expResult = {}
relaEx = {}
# set thresholds
for th in range(0, 51, 5):
expResult[th] = copy.deepcopy(partAns)
relaEx[th] = []
print "worker %d build expResult" % (jobid)
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
#targetName = ans["_id"].replace("(","").replace(")","").split("_") # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["observed"]
# origin properties, 理論上應該會比 observed 還要多
originRela = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
# TODO
# Relation extraction
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
ptntks = table[ptnId]["pattern"]
lineText = article[line[0]]
if not projizz.isPatternValidate(
ptnId, table, confidence=confidence, st=st):
continue
rfp = table[ptnId]["relations"]
# check degree
if len(rfp) > 5:
continue
# if no support, ignore this pattern
if st[ptnId][0][1]["support"] <= 0:
continue
# TODO - Modlify string, remove pattern text in string?
cosRlt = projizz.vsmSimilarity(lineText,
vsmData,
relas=rfp,
ptntext=ptntks)
# NOTE - if cosine value > threshold then there is a relation (?)
for keyname in expResult:
threshold = float(keyname) / 100.0
for pr in cosRlt:
# Check type
if domainRange[pr]["domain"] in types:
if cosRlt[pr] > threshold:
if pr not in relaEx[keyname]:
relaEx[keyname].append(pr)
#### Evaluation
for keyname in expResult:
for attribute in expResult[keyname]:
# special case, ignore.
if attribute == "produced":
continue
postive = False
true = False
if attribute in relaEx[keyname]:
postive = True
if attribute in relation:
true = True
if true:
if postive:
expResult[keyname][attribute]["tp"].append(
ans["revid"])
else:
expResult[keyname][attribute]["fn"].append(
ans["revid"])
else:
if postive:
expResult[keyname][attribute]["fp"].append(
ans["revid"])
else:
# ignore true-negative
pass
if count % 100 == 0:
print "worker #%d done %d." % (jobid, count)
return expResult
def mapper(jobid,filename,inputPath,inputPtnPath,model,table):
# Read article
contentJson = projizz.jsonRead( os.path.join(inputPath,filename) )
# Read ptn
contentPtnJson = projizz.jsonRead( os.path.join(inputPtnPath,filename) )
print "Worker %d : Read %s into filter" % (jobid,filename)
### Connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid":{"$in":queries}})
print "worker %d query=%d, result=%d" % (jobid,len(queries),itr.count())
count = 0
supportInstanceByFile = {}
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"])
relation = ans["observed"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
supportInstanceByFile[key] = {}
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
if not projizz.isPatternValidate(ptnId, table):
continue
for rela in table[ptnId]["relations"]:
# it's a support instance
if rela in relation:
if not ptnId in supportInstanceByFile[key]:
supportInstanceByFile[key][ptnId] = {}
if not rela in supportInstanceByFile[key][ptnId]:
supportInstanceByFile[key][ptnId][rela] = []
if not line[0] in supportInstanceByFile[key][ptnId][rela]:
supportInstanceByFile[key][ptnId][rela].append(line[0])
for ptnId in supportInstanceByFile[key]:
for rela in supportInstanceByFile[key][ptnId]:
lines = supportInstanceByFile[key][ptnId][rela]
supportInstanceByFile[key][ptnId][rela] = []
for lineN in lines:
supportInstanceByFile[key][ptnId][rela].append(article[lineN])
if count % 100 == 0:
print "worker #%d done %d." % (jobid,count)
return supportInstanceByFile
def mapper(jobid, filename, inputPath, inputPtnPath, table, st, partAns,
domainRange, confidence, nbcPath):
# read articles and patterns
contentJson = projizz.jsonRead(os.path.join(inputPath, filename))
contentPtnJson = projizz.jsonRead(os.path.join(inputPtnPath, filename))
classifiers = projizz.getNBClassifiers(nbcPath)
print "Worker %d : Read %s" % (jobid, filename)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid": {"$in": queries}})
print "worker %d query=%d, result=%d" % (jobid, len(queries), itr.count())
count = 0
expResult = partAns
relaEx = []
print "worker %d build expResult" % (jobid)
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
#targetName = ans["_id"].replace("(","").replace(")","").split("_") # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["observed"]
# origin properties, 理論上應該會比 observed 還要多
originRela = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
# Relation extraction
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
if lineText[
0] == "^": # It's a wikipeida reference comments, ignore it!
continue
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
ptntks = table[ptnId]["pattern"]
if not projizz.isPatternValidate(
ptnId, table, confidence=confidence, st=st):
continue
rfp = table[ptnId]["relations"]
# check degree
if len(rfp) > 5:
continue
# if no support, ignore this pattern
if st[ptnId][0][1]["support"] <= 0:
continue
for ptnst in st[ptnId]:
# ptnst[0] = relation
# ptnst[1] = {"support":,"total": }
if domainRange[ptnst[0]] not in types:
continue
if classifiers[ptnst[0]] == None:
continue
if classifiers[ptnst[0]].classify(lineText) == "pos":
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
#### Evaluation
for attribute in expResult:
# special case, ignore.
if attribute == "produced":
continue
postive = False
true = False
if attribute in relaEx:
postive = True
if attribute in relation:
true = True
if true:
if postive:
expResult[attribute]["tp"].append(ans["revid"])
else:
expResult[attribute]["fn"].append(ans["revid"])
else:
if postive:
expResult[attribute]["fp"].append(ans["revid"])
else:
# ignore true-negative
pass
if count % 100 == 0:
print "worker #%d done %d." % (jobid, count)
return expResult
def filterFunction(jobid,filename,inputPtnPath,model,table,partAns,st,domainRange,inputPath,confidence,nbcPath):
# read patterns in articles
contentPtnJson = json.load(open(os.path.join(inputPtnPath,filename),"r"))
contentJson = projizz.jsonRead(os.path.join(inputPath,filename))
classifiers = projizz.getNBClassifiers(nbcPath)
print "Worker %d : Read %s into filter" % (jobid,filename)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid":{"$in":queries}})
print "worker %d query=%d, result=%d" % (jobid,len(queries),itr.count())
count = 0
# prepare keys for multiple-exp
# degree: 1 ~ 5
# ambigu: select 1, select n (threshold:.5, .75), select all
# type or not: no type info, type info
expResult = {}
for deg in range(1,6):
for typ in ["n","t"]:
if not deg == 1:
for amb in ["one","50","75","all"]:
keyname = "%d-%s-%s" % (deg,amb,typ)
expResult[keyname] = copy.deepcopy(partAns)
else:
keyname = "%d-1-%s" % (deg,typ)
expResult[keyname] = copy.deepcopy(partAns)
print "worker %d build expResult" % (jobid)
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
#targetName = ans["_id"].replace("(","").replace(")","").split("_") # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["observed"]
# origin properties, 理論上應該會比 observed 還要多
originRela = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
for keyname in expResult:
args = keyname.split("-")
degree = int(args[0])
ambigu = args[1]
typ = args[2]
# Relation extraction
relaEx = []
ptnExRela = {} # rela: ptns
def recordPtnMakeRela(ptnId,rela,record):
if not rela in record:
record[rela] = []
if not ptnId in record[rela]:
record[rela].append(ptnId)
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
if lineText[0] == "^": # It's a wikipeida reference comments, ignore it!
continue
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
# validate the pattern
if not projizz.isPatternValidate(ptnId, table, confidence=confidence, st=st):
continue
# get all possible relation of this pattern
rfp = table[ptnId]["relations"]
# check degree
if len(rfp) > degree:
continue
#
# Decide to choice relation
#
if len(rfp) == 1: # or degree == 1
if st[ptnId][0][1]["support"] > 0 and not rfp[0] in relaEx:
if typ == "t":
if domainRange[rfp[0]]["domain"] in types:
pr = rfp[0]
if not classifiers[pr] == None and classifiers[pr].classify(lineText) == "pos":
relaEx.append(rfp[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, rfp[0], ptnExRela)
else:
pr = rfp[0]
if not classifiers[pr] == None and classifiers[pr].classify(lineText) == "pos":
relaEx.append(rfp[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, rfp[0], ptnExRela)
else:
if ambigu == "one":
if typ == "t":
for ptnst in st[ptnId]:
# ptnst[0] = relation
# ptnst[1] = {"support": , "total": }
if ptnst[1]["support"] > 0 and domainRange[ptnst[0]]["domain"] in types:
if not ptnst[0] in relaEx and not classifiers[ptnst[0]] == None and classifiers[ptnst[0]].classify(lineText) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, ptnst[0], ptnExRela)
break
else:
if st[ptnId][0][1]["support"] > 0 and not rfp[0] in relaEx and not classifiers[rfp[0]] == None and classifiers[rfp[0]].classify(lineText) == "pos":
relaEx.append(rfp[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, rfp[0], ptnExRela)
elif ambigu == "all":
for ptnst in st[ptnId]:
if typ == "t":
if domainRange[ptnst[0]]["domain"] in types:
if not ptnst[0] in relaEx and not classifiers[ptnst[0]] == None and classifiers[ptnst[0]].classify(lineText) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, ptnst[0], ptnExRela)
else:
if not ptnst[0] in relaEx and not classifiers[ptnst[0]] == None and classifiers[ptnst[0]].classify(lineText) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, ptnst[0], ptnExRela)
else:
th = 0.75
if ambigu == "50":
th = 0.5
b = st[ptnId][0][1]["support"]
if b > 0:
for ptnst in st[ptnId]:
if float(ptnst[1]["support"])/float(b) >= th:
if typ == "t":
if domainRange[ptnst[0]]["domain"] in types and not ptnst[0] in relaEx and not classifiers[ptnst[0]] == None and classifiers[ptnst[0]].classify(lineText) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, ptnst[0], ptnExRela)
else:
if not ptnst[0] in relaEx and not classifiers[ptnst[0]] == None and classifiers[ptnst[0]].classify(lineText) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, ptnst[0], ptnExRela)
# Evaluation
for attribute in expResult[keyname]:
# special case, ignore.
if attribute == "produced":
continue
postive = False
true = False
if attribute in relaEx:
postive = True
if attribute in relation:
true = True
if true:
if postive:
expResult[keyname][attribute]["tp"].append(ans["revid"])
else:
expResult[keyname][attribute]["fn"].append(ans["revid"])
else:
if postive:
# False Positive
expResult[keyname][attribute]["fp"].append(ans["revid"])
# TODO - 分析錯誤原因
if attribute in ptnExRela:
if attribute in originRela:
# type 2 error
expResult[keyname][attribute]["et2"].append(ans["revid"])
else:
found = False
ptns = ptnExRela[attribute] # get the patterns raise the Relation
for pid in ptns:
for psbR in table[pid]["relations"]:
if psbR == attribute:
continue
# here means that the pattern can raise a `correct' relation in answer, may it choice or not
if domainRange[psbR]["domain"] in types and psbR in relation:
found = True
break
if found:
# type 1 error
expResult[keyname][attribute]["et1"].append(ans["revid"])
else:
# type 3 error
expResult[keyname][attribute]["et3"].append(ans["revid"])
else:
# 這是什麼情況？@@ 這種狀況基`本不可能發生吧XD
pass
else:
# ignore true-negative
pass
if count % 100 == 0:
print "worker #%d done %d." % (jobid,count)
return expResult
def main(part,revid):
# Paths (on NLG workstation)
inputPath = "/tmp2/ccli/y-part-%s/" % (part)
inputPtnPath = "/tmp2/ccli/y-ptn-part-%s/" % (part)
spPath = "../yago/yagoPSv2/ps.%s.json" % (part)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
itr = collection.find({"revid":revid})
# find filename
a = os.popen("grep -nr \"%s\" %s" % (revid,inputPath)).readline()
targetFilename = a.split(":")[0].split("/")[-1]
key = "%s.txt" % (revid)
pattern = projizz.jsonRead(inputPtnPath+targetFilename)[key]
article = projizz.articleSimpleSentenceFileter(projizz.jsonRead(inputPath+targetFilename)[key])
st = projizz.getSortedPatternStatistic(projizz.jsonRead(spPath))
domainRange = projizz.getYagoRelationDomainRange();
model, table = projizz.readPrefixTreeModelWithTable("../yago/yagoPatternTree.model","../yago/yagoPatternTree.table")
print "Part %s, RevID=%s, in %s" % (part,revid,targetFilename)
for ans in itr:
targetName = ans["_id"].replace("(","").replace(")","").split("_") # get entity name's part
types = ans["type"]
answers = ans["observed"]
print "Target=%s\nTarget token=%s" % (ans["_id"].encode("utf-8"),targetName)
print "Type=%s" % (types)
print "Answer=%s" % (answers)
for line in pattern:
lineText = article[line[0]]
named = False
for namedToken in targetName:
if namedToken in lineText:
named = True
break
if not named: # No target name in line text
continue # go to next line.
for ptn in line[1]:
ptnId = "%d" % (ptn[0])
#rfp = table[ptnId]["relations"]
if not ptnId in st:
continue
for ps in st[ptnId]:
if float(ps[1]["support"])/float(ps[1]["total"]) > 0:
if domainRange[ps[0]]["domain"] in types:
print "#%d" % (line[0]),lineText.encode("utf-8")
isIn = "(X)"
if ps[0] in answers:
isIn = "(O)"
print "%s %s/%s/{%d,%d}/ %s" % (isIn,ptnId,table[ptnId]["pattern"],ps[1]["support"],ps[1]["total"],ps[0])
pass
# select top 1
break
# prevent second ans
break
def mapper(jobid, filename, inputPath, inputPtnPath, model, table):
# Read article
contentJson = projizz.jsonRead(os.path.join(inputPath, filename))
# Read ptn
contentPtnJson = projizz.jsonRead(os.path.join(inputPtnPath, filename))
print "Worker %d : Read %s into filter" % (jobid, filename)
### Connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid": {"$in": queries}})
print "worker %d query=%d, result=%d" % (jobid, len(queries), itr.count())
count = 0
supportInstanceByFile = {}
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"])
relation = ans["observed"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
supportInstanceByFile[key] = {}
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
if not projizz.isPatternValidate(ptnId, table):
continue
for rela in table[ptnId]["relations"]:
# it's a support instance
if rela in relation:
if not ptnId in supportInstanceByFile[key]:
supportInstanceByFile[key][ptnId] = {}
if not rela in supportInstanceByFile[key][ptnId]:
supportInstanceByFile[key][ptnId][rela] = []
if not line[0] in supportInstanceByFile[key][ptnId][
rela]:
supportInstanceByFile[key][ptnId][rela].append(
line[0])
for ptnId in supportInstanceByFile[key]:
for rela in supportInstanceByFile[key][ptnId]:
lines = supportInstanceByFile[key][ptnId][rela]
supportInstanceByFile[key][ptnId][rela] = []
for lineN in lines:
supportInstanceByFile[key][ptnId][rela].append(
article[lineN])
if count % 100 == 0:
print "worker #%d done %d." % (jobid, count)
return supportInstanceByFile
def filterFunction(jobid, filename, inputPtnPath, model, table, partAns, st,
domainRange, inputPath, confidence, nbcPath):
# read patterns in articles
contentPtnJson = json.load(open(os.path.join(inputPtnPath, filename), "r"))
contentJson = projizz.jsonRead(os.path.join(inputPath, filename))
classifiers = projizz.getNBClassifiers(nbcPath)
print "Worker %d : Read %s into filter" % (jobid, filename)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid": {"$in": queries}})
print "worker %d query=%d, result=%d" % (jobid, len(queries), itr.count())
count = 0
# prepare keys for multiple-exp
# degree: 1 ~ 5
# ambigu: select 1, select n (threshold:.5, .75), select all
# type or not: no type info, type info
expResult = {}
for deg in range(1, 6):
for typ in ["n", "t"]:
if not deg == 1:
for amb in ["one", "50", "75", "all"]:
keyname = "%d-%s-%s" % (deg, amb, typ)
expResult[keyname] = copy.deepcopy(partAns)
else:
keyname = "%d-1-%s" % (deg, typ)
expResult[keyname] = copy.deepcopy(partAns)
print "worker %d build expResult" % (jobid)
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
#targetName = ans["_id"].replace("(","").replace(")","").split("_") # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["observed"]
# origin properties, 理論上應該會比 observed 還要多
originRela = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
for keyname in expResult:
args = keyname.split("-")
degree = int(args[0])
ambigu = args[1]
typ = args[2]
# Relation extraction
relaEx = []
ptnExRela = {} # rela: ptns
def recordPtnMakeRela(ptnId, rela, record):
if not rela in record:
record[rela] = []
if not ptnId in record[rela]:
record[rela].append(ptnId)
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
if lineText[
0] == "^": # It's a wikipeida reference comments, ignore it!
continue
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
# validate the pattern
if not projizz.isPatternValidate(
ptnId, table, confidence=confidence, st=st):
continue
# get all possible relation of this pattern
rfp = table[ptnId]["relations"]
# check degree
if len(rfp) > degree:
continue
#
# Decide to choice relation
#
if len(rfp) == 1: # or degree == 1
if st[ptnId][0][1]["support"] > 0 and not rfp[
0] in relaEx:
if typ == "t":
if domainRange[rfp[0]]["domain"] in types:
pr = rfp[0]
if not classifiers[
pr] == None and classifiers[
pr].classify(
lineText) == "pos":
relaEx.append(rfp[0])
# FIXME For error checking
recordPtnMakeRela(
ptnId, rfp[0], ptnExRela)
else:
pr = rfp[0]
if not classifiers[pr] == None and classifiers[
pr].classify(lineText) == "pos":
relaEx.append(rfp[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, rfp[0], ptnExRela)
else:
if ambigu == "one":
if typ == "t":
for ptnst in st[ptnId]:
# ptnst[0] = relation
# ptnst[1] = {"support": , "total": }
if ptnst[1]["support"] > 0 and domainRange[
ptnst[0]]["domain"] in types:
if not ptnst[
0] in relaEx and not classifiers[
ptnst[
0]] == None and classifiers[
ptnst[0]].classify(
lineText
) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(
ptnId, ptnst[0], ptnExRela)
break
else:
if st[ptnId][0][1]["support"] > 0 and not rfp[
0] in relaEx and not classifiers[
rfp[0]] == None and classifiers[
rfp[0]].classify(
lineText) == "pos":
relaEx.append(rfp[0])
# FIXME For error checking
recordPtnMakeRela(ptnId, rfp[0], ptnExRela)
elif ambigu == "all":
for ptnst in st[ptnId]:
if typ == "t":
if domainRange[
ptnst[0]]["domain"] in types:
if not ptnst[
0] in relaEx and not classifiers[
ptnst[
0]] == None and classifiers[
ptnst[0]].classify(
lineText
) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(
ptnId, ptnst[0], ptnExRela)
else:
if not ptnst[
0] in relaEx and not classifiers[
ptnst[
0]] == None and classifiers[
ptnst[0]].classify(
lineText) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(
ptnId, ptnst[0], ptnExRela)
else:
th = 0.75
if ambigu == "50":
th = 0.5
b = st[ptnId][0][1]["support"]
if b > 0:
for ptnst in st[ptnId]:
if float(ptnst[1]["support"]) / float(
b) >= th:
if typ == "t":
if domainRange[ptnst[0]][
"domain"] in types and not ptnst[
0] in relaEx and not classifiers[
ptnst[0]] == None and classifiers[
ptnst[
0]].classify(
lineText
) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(
ptnId, ptnst[0], ptnExRela)
else:
if not ptnst[0] in relaEx and not classifiers[
ptnst[
0]] == None and classifiers[
ptnst[0]].classify(
lineText
) == "pos":
relaEx.append(ptnst[0])
# FIXME For error checking
recordPtnMakeRela(
ptnId, ptnst[0], ptnExRela)
# Evaluation
for attribute in expResult[keyname]:
# special case, ignore.
if attribute == "produced":
continue
postive = False
true = False
if attribute in relaEx:
postive = True
if attribute in relation:
true = True
if true:
if postive:
expResult[keyname][attribute]["tp"].append(
ans["revid"])
else:
expResult[keyname][attribute]["fn"].append(
ans["revid"])
else:
if postive:
# False Positive
expResult[keyname][attribute]["fp"].append(
ans["revid"])
# TODO - 分析錯誤原因
if attribute in ptnExRela:
if attribute in originRela:
# type 2 error
expResult[keyname][attribute]["et2"].append(
ans["revid"])
else:
found = False
ptns = ptnExRela[
attribute] # get the patterns raise the Relation
for pid in ptns:
for psbR in table[pid]["relations"]:
if psbR == attribute:
continue
# here means that the pattern can raise a `correct' relation in answer, may it choice or not
if domainRange[psbR][
"domain"] in types and psbR in relation:
found = True
break
if found:
# type 1 error
expResult[keyname][attribute][
"et1"].append(ans["revid"])
else:
# type 3 error
expResult[keyname][attribute][
"et3"].append(ans["revid"])
else:
# 這是什麼情況？@@ 這種狀況基`本不可能發生吧XD
pass
else:
# ignore true-negative
pass
if count % 100 == 0:
print "worker #%d done %d." % (jobid, count)
return expResult
def mapper(jobid, filename, inputPath, inputPtnPath, model, table, confidence):
# Read article
contentJson = projizz.jsonRead(os.path.join(inputPath, filename))
# Read ptn
contentPtnJson = projizz.jsonRead(os.path.join(inputPtnPath, filename))
print "Worker %d : Read %s into filter" % (jobid, filename)
### Connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid": {"$in": queries}})
print "worker %d query=%d, result=%d" % (jobid, len(queries), itr.count())
count = 0
supportInstanceByFile = {}
linesByRelations = {}
linesNoRelaByRelations = {}
POS = {}
NEG = {}
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"])
relation = ans["observed"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
supportInstanceByFile[key] = {}
linesByRela = {}
linesByNoRela = {}
pos = {}
neg = {}
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
if not projizz.isPatternValidate(
ptnId, table, confidence=confidence):
continue
# give up degree > 5 's pattern
if len(table[ptnId]["relations"]) > 5:
continue
for rela in table[ptnId]["relations"]:
# it's a support instance
if rela in relation:
# NOTE - remove pattern text.
if not rela in linesByRela:
linesByRela[rela] = {}
if not line[0] in linesByRela[rela]:
linesByRela[rela][line[0]] = []
if not ptnId in linesByRela[rela][line[0]]:
linesByRela[rela][line[0]].append(ptnId)
# For binary classifier
if not rela in pos:
pos[rela] = []
if not lineText[0] == "^" and line[0] not in pos[rela]:
pos[rela].append(line[0])
else:
if not rela in linesByNoRela:
linesByNoRela[rela] = {}
if not line[0] in linesByNoRela[rela]:
linesByNoRela[rela][line[0]] = []
if not ptnId in linesByNoRela[rela][line[0]]:
linesByNoRela[rela][line[0]].append(ptnId)
# For binary classifier
if not rela in neg:
neg[rela] = []
if not lineText[0] == "^" and line[0] not in neg[rela]:
neg[rela].append(line[0])
for rela in linesByRela:
if not rela in linesByRelations:
linesByRelations[rela] = []
for lineN in linesByRela[rela]:
text = projizz.getTokens(article[lineN].lower())
for ptnId in linesByRela[rela][lineN]:
ptntext = table[ptnId]["pattern"].split()
for ptntk in ptntext:
if ptntk in text:
text.remove(ptntk)
l = ' '.join(text)
linesByRelations[rela].append(l)
for rela in linesByNoRela:
if not rela in linesNoRelaByRelations:
linesNoRelaByRelations[rela] = []
for lineN in linesByNoRela[rela]:
text = projizz.getTokens(article[lineN].lower())
for ptnId in linesByNoRela[rela][lineN]:
ptntext = table[ptnId]["pattern"].split()
for ptntk in ptntext:
if ptntk in text:
text.remove(ptntk)
l = ' '.join(text)
linesNoRelaByRelations[rela].append(l)
# For binary classifier
for rela in pos:
if not rela in POS:
POS[rela] = []
for lineN in pos[rela]:
POS[rela].append({"text": article[lineN], "label": "pos"})
for rela in neg:
if not rela in NEG:
NEG[rela] = []
for lineN in neg[rela]:
NEG[rela].append({"text": article[lineN], "label": "neg"})
if count % 100 == 0:
print "worker #%d done %d." % (jobid, count)
return linesByRelations, linesNoRelaByRelations, POS, NEG
def filterFunction(jobid, filename, inputPtnPath, model, table, partAns, st,
domainRange, inputPath):
# read patterns in articles
contentPtnJson = json.load(open(os.path.join(inputPtnPath, filename), "r"))
# read articles
contentJson = json.load(open(os.path.join(inputPath, filename), "r"))
print "Worker %d : Read %s into filter" % (jobid, filename)
politicalPosition = [
"Secretary", "Premier", "Mayor", "Captain", "Minister", "Chief",
"Governor", "General", "Ambassadors", "Member"
]
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid": {"$in": queries}})
print "worker %d query=%d, result=%d" % (jobid, len(queries), itr.count())
count = 0
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
targetName = projizz.getNamedEntityTokens(
ans["_id"]) # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
relaEx = []
for line in ptnEx: # line[0]: line number
lineText = article[line[0]]
named = False
for namedToken in targetName:
if namedToken in lineText:
named = True
break
if not named: # No target name in line text
continue # go to next line.
for ptn in line[1]: # line[1]: array of patterns
ptnId = "%d" % (ptn[0]
) # ptn[0]: pattern ID, [1]: start, [2]: end
rfp = table[ptnId]["relations"]
# ignore non-used pattern
if not table[ptnId]["used"]:
continue
if "eval" in table[ptnId] and not table[ptnId]["eval"]:
continue
# never seen pattern
if not ptnId in st:
continue
# if only one relation
if len(rfp) < 2:
if "holdsPoliticalPosition" in rfp:
foundPosition = False
for position in politicalPosition:
if position in lineText and not "holdsPoliticalPosition" in relaEx:
relaEx.append("holdsPoliticalPosition")
break
if foundPosition:
continue
if st[ptnId][0][1]["support"] > 0 and not rfp[0] in relaEx:
relaEx.append(rfp[0])
# more than one relation
else:
if "holdsPoliticalPosition" in rfp:
foundPosition = False
for position in politicalPosition:
if position in lineText and not "holdsPoliticalPosition" in relaEx:
relaEx.append("holdsPoliticalPosition")
break
if foundPosition:
continue
# using the first as the answer
if st[ptnId][0][1]["support"] > 0 and not rfp[0] in relaEx:
relaEx.append(rfp[0])
# Remove impossible relations
toBeRemove = []
for attribute in relaEx:
# speical case, produced
if domainRange[attribute] == "":
continue
if not domainRange[attribute]["domain"] in types:
if not attribute in toBeRemove:
toBeRemove.append(attribute)
for attribute in toBeRemove:
relaEx.remove(attribute)
# Evaluation
for attribute in partAns:
postive = False
true = False
if attribute in relaEx:
postive = True
if attribute in relation:
true = True
if true:
if postive:
partAns[attribute]["tp"].append(ans["revid"])
else:
partAns[attribute]["fn"].append(ans["revid"])
else:
if postive:
partAns[attribute]["fp"].append(ans["revid"])
else:
partAns[attribute]["tn"].append(ans["revid"])
if count % 100 == 0:
print "worker #%d done %d." % (jobid, count)
return partAns
def updateAnswer(jobid,inputPath,filename):
contenJson = projizz.jsonRead(os.path.join(inputPath,filename))
print "#%d - %s" % (jobid,filename)
connect = Connection()
answerCollection = connect.projizz.result.yago.answer
factCollection = connect.projizz.yago.facts
queries = map(lambda x: x[:-4], contenJson)
itr = answerCollection.find({"revid":{"$in":queries}})
print "#%d - query=%d,result=%d" % (jobid,len(queries),itr.count())
count = 0
ty1g = 0
ty2g = 0
updateC = 0
articles = []
for ans in itr:
count += 1
articleID = "%s.txt" % (ans["revid"])
articleName = ans["_id"]
properties = ans["properties"]
#not consider references.
#references = ans["references"]
if len(properties) == 0:
# give up those no properties' article
# print "#%d - give up %s (1)" % (jobid,articleID)
ty1g += 1
continue
needUpdate = len(properties)
lines = projizz.articleSimpleSentenceFileter(contenJson[articleID])
text = ""
for line in lines:
text += (line + " ")
observed = []
for pro in properties:
pitr = factCollection.find({"property":pro,"subject":articleName})
if pitr.count() < 1:
notNeed.append(pro)
continue
found = False
for fact in pitr:
tokens = projizz.getNamedEntityTokens(fact["object"])
for token in tokens:
if token in text:
found = True
break
if found:
break
if found:
observed.append(pro)
if len(observed) > 0:
articles.append(articleID)
ans["observed"] = observed
answerCollection.update({"revid":ans["revid"]},ans,upsert=False)
else:
ty2g += 1
#print "#%d - give up %s (2)" % (jobid,articleID)
print "#%d -> update %d (give up %d + %d)" % (jobid,len(articles),ty1g,ty2g)
return (filename,articles)
def mapper(jobid,filename,inputPath,inputPtnPath,model,table,confidence):
# Read article
contentJson = projizz.jsonRead( os.path.join(inputPath,filename) )
# Read ptn
contentPtnJson = projizz.jsonRead( os.path.join(inputPtnPath,filename) )
print "Worker %d : Read %s into filter" % (jobid,filename)
### Connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid":{"$in":queries}})
print "worker %d query=%d, result=%d" % (jobid,len(queries),itr.count())
count = 0
supportInstanceByFile = {}
linesByRelations = {}
linesNoRelaByRelations = {}
POS = {}
NEG = {}
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"])
relation = ans["observed"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
supportInstanceByFile[key] = {}
linesByRela = {}
linesByNoRela = {}
pos = {}
neg = {}
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
if not projizz.isPatternValidate(ptnId, table, confidence=confidence):
continue
# give up degree > 5 's pattern
if len(table[ptnId]["relations"]) > 5:
continue
for rela in table[ptnId]["relations"]:
# it's a support instance
if rela in relation:
# NOTE - remove pattern text.
if not rela in linesByRela:
linesByRela[rela] = {}
if not line[0] in linesByRela[rela]:
linesByRela[rela][line[0]] = []
if not ptnId in linesByRela[rela][line[0]]:
linesByRela[rela][line[0]].append(ptnId)
# For binary classifier
if not rela in pos:
pos[rela] = []
if not lineText[0] == "^" and line[0] not in pos[rela]:
pos[rela].append(line[0])
else:
if not rela in linesByNoRela:
linesByNoRela[rela] = {}
if not line[0] in linesByNoRela[rela]:
linesByNoRela[rela][line[0]] = []
if not ptnId in linesByNoRela[rela][line[0]]:
linesByNoRela[rela][line[0]].append(ptnId)
# For binary classifier
if not rela in neg:
neg[rela] = []
if not lineText[0] == "^" and line[0] not in neg[rela]:
neg[rela].append(line[0])
for rela in linesByRela:
if not rela in linesByRelations:
linesByRelations[rela] = []
for lineN in linesByRela[rela]:
text = projizz.getTokens( article[lineN].lower() )
for ptnId in linesByRela[rela][lineN]:
ptntext = table[ptnId]["pattern"].split()
for ptntk in ptntext:
if ptntk in text:
text.remove(ptntk)
l = ' '.join(text)
linesByRelations[rela].append(l)
for rela in linesByNoRela:
if not rela in linesNoRelaByRelations:
linesNoRelaByRelations[rela] = []
for lineN in linesByNoRela[rela]:
text = projizz.getTokens( article[lineN].lower() )
for ptnId in linesByNoRela[rela][lineN]:
ptntext = table[ptnId]["pattern"].split()
for ptntk in ptntext:
if ptntk in text:
text.remove(ptntk)
l = ' '.join(text)
linesNoRelaByRelations[rela].append(l)
# For binary classifier
for rela in pos:
if not rela in POS:
POS[rela] = []
for lineN in pos[rela]:
POS[rela].append( {"text":article[lineN],"label":"pos"} )
for rela in neg:
if not rela in NEG:
NEG[rela] = []
for lineN in neg[rela]:
NEG[rela].append( {"text":article[lineN],"label":"neg"} )
if count % 100 == 0:
print "worker #%d done %d." % (jobid,count)
return linesByRelations,linesNoRelaByRelations,POS,NEG
def filterFunction(jobid,filename,inputPtnPath,model,table,partAns,st,domainRange,inputPath,confidence):
# read patterns in articles
contentPtnJson = json.load(open(os.path.join(inputPtnPath,filename),"r"))
contentJson = projizz.jsonRead(os.path.join(inputPath,filename))
print "Worker %d : Read %s into filter" % (jobid,filename)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid":{"$in":queries}})
print "worker %d query=%d, result=%d" % (jobid,len(queries),itr.count())
count = 0
# prepare keys for multiple-exp
# degree: 1 ~ 5
# ambigu: select 1, select n (threshold:.5, .75), select all
# type or not: no type info, type info
expResult = {}
for deg in range(1,6):
for typ in ["n","t"]:
if not deg == 1:
for amb in ["one","50","75","all"]:
keyname = "%d-%s-%s" % (deg,amb,typ)
expResult[keyname] = copy.deepcopy(partAns)
else:
keyname = "%d-1-%s" % (deg,typ)
expResult[keyname] = copy.deepcopy(partAns)
print "worker %d build expResult" % (jobid)
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
#targetName = ans["_id"].replace("(","").replace(")","").split("_") # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["observed"]
# origin properties, 理論上應該會比 observed 還要多
originRela = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
for keyname in expResult:
args = keyname.split("-")
degree = int(args[0])
ambigu = args[1]
typ = args[2]
# Relation extraction
relaEx = []
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
if lineText[0] == "^": # It's a wikipeida reference comments, ignore it!
continue
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
if not projizz.isPatternValidate(ptnId, table, confidence=confidence, st=st):
continue
rfp = table[ptnId]["relations"]
# check degree
if len(rfp) > degree:
continue
if len(rfp) == 1: # or degree == 1
if st[ptnId][0][1]["support"] > 0 and not rfp[0] in relaEx:
if typ == "t":
if domainRange[rfp[0]]["domain"] in types:
relaEx.append(rfp[0])
else:
relaEx.append(rfp[0])
else:
if ambigu == "one":
if typ == "t":
for ptnst in st[ptnId]:
# ptnst[0] = relation
# ptnst[1] = {"support": , "total": }
if ptnst[1]["support"] > 0 and domainRange[ptnst[0]]["domain"] in types:
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
break
else:
if st[ptnId][0][1]["support"] > 0 and not rfp[0] in relaEx:
relaEx.append(rfp[0])
elif ambigu == "all":
for ptnst in st[ptnId]:
if typ == "t":
if domainRange[ptnst[0]]["domain"] in types:
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
else:
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
else:
th = 0.75
if ambigu == "50":
th = 0.5
b = st[ptnId][0][1]["support"]
if b > 0:
for ptnst in st[ptnId]:
if float(ptnst[1]["support"])/float(b) >= th:
if typ == "t":
if domainRange[ptnst[0]]["domain"] in types and not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
else:
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
# Evaluation
for attribute in expResult[keyname]:
# special case, ignore.
if attribute == "produced":
continue
postive = False
true = False
if attribute in relaEx:
postive = True
if attribute in relation:
true = True
if true:
if postive:
expResult[keyname][attribute]["tp"].append(ans["revid"])
else:
expResult[keyname][attribute]["fn"].append(ans["revid"])
else:
if postive:
expResult[keyname][attribute]["fp"].append(ans["revid"])
else:
# ignore true-negative
pass
if count % 100 == 0:
print "worker #%d done %d." % (jobid,count)
return expResult
def mapper(jobid, filename, inputPath, inputPtnPath, table, st, partAns, domainRange, confidence, vsmData):
# read articles and patterns
contentJson = projizz.jsonRead(os.path.join(inputPath,filename))
contentPtnJson = projizz.jsonRead(os.path.join(inputPtnPath,filename))
print "Worker %d : Read %s" % (jobid,filename)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid":{"$in":queries}})
print "worker %d query=%d, result=%d" % (jobid,len(queries),itr.count())
count = 0
expResult = {}
relaEx = {}
# set thresholds
for th in range(0,51,5):
expResult[th] = copy.deepcopy(partAns)
relaEx[th] = []
print "worker %d build expResult" % (jobid)
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
#targetName = ans["_id"].replace("(","").replace(")","").split("_") # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["observed"]
# origin properties, 理論上應該會比 observed 還要多
originRela = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
# TODO
# Relation extraction
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
ptntks = table[ptnId]["pattern"]
lineText = article[line[0]]
if not projizz.isPatternValidate(ptnId, table, confidence=confidence, st=st):
continue
rfp = table[ptnId]["relations"]
# check degree
if len(rfp) > 5:
continue
# if no support, ignore this pattern
if st[ptnId][0][1]["support"] <= 0:
continue
# TODO - Modlify string, remove pattern text in string?
cosRlt = projizz.vsmSimilarity( lineText, vsmData, relas=rfp, ptntext=ptntks )
# NOTE - if cosine value > threshold then there is a relation (?)
for keyname in expResult:
threshold = float(keyname)/100.0
for pr in cosRlt:
# Check type
if domainRange[pr]["domain"] in types:
if cosRlt[pr] > threshold:
if pr not in relaEx[keyname]:
relaEx[keyname].append(pr)
#### Evaluation
for keyname in expResult:
for attribute in expResult[keyname]:
# special case, ignore.
if attribute == "produced":
continue
postive = False
true = False
if attribute in relaEx[keyname]:
postive = True
if attribute in relation:
true = True
if true:
if postive:
expResult[keyname][attribute]["tp"].append(ans["revid"])
else:
expResult[keyname][attribute]["fn"].append(ans["revid"])
else:
if postive:
expResult[keyname][attribute]["fp"].append(ans["revid"])
else:
# ignore true-negative
pass
if count % 100 == 0:
print "worker #%d done %d." % (jobid,count)
return expResult
def main(part, revid):
# Paths (on NLG workstation)
inputPath = "/tmp2/ccli/yago-part-%s/" % (part)
inputPtnPath = "/tmp2/ccli/yago-ptn-part-%s/" % (part)
spPath = "../yago/yagoPSv1/ps.%s.json" % (part)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
itr = collection.find({"revid": revid})
# find filename
a = os.popen("grep -nr \"%s\" %s" % (revid, inputPath)).readline()
targetFilename = a.split(":")[0].split("/")[-1]
key = "%s.txt" % (revid)
pattern = projizz.jsonRead(inputPtnPath + targetFilename)[key]
article = projizz.articleSimpleSentenceFileter(
projizz.jsonRead(inputPath + targetFilename)[key])
st = projizz.getSortedPatternStatistic(projizz.jsonRead(spPath))
domainRange = projizz.getYagoRelationDomainRange()
model, table = projizz.readPrefixTreeModelWithTable(
"../yago/yagoPatternTree.model", "../yago/yagoPatternTree.table")
print "Part %s, RevID=%s, in %s" % (part, revid, targetFilename)
for ans in itr:
targetName = ans["_id"].replace("(", "").replace(")", "").split(
"_") # get entity name's part
types = ans["type"]
answers = ans["properties"]
print "Target=%s\nTarget token=%s" % (ans["_id"].encode("utf-8"),
targetName)
print "Type=%s" % (types)
print "Answer=%s" % (answers)
for line in pattern:
lineText = article[line[0]]
named = False
for namedToken in targetName:
if namedToken in lineText:
named = True
break
if not named: # No target name in line text
continue # go to next line.
for ptn in line[1]:
ptnId = "%d" % (ptn[0])
#rfp = table[ptnId]["relations"]
if not ptnId in st:
continue
for ps in st[ptnId]:
if float(ps[1]["support"]) / float(ps[1]["total"]) > 0:
if domainRange[ps[0]]["domain"] in types:
print "#%d" % (line[0]), lineText.encode("utf-8")
isIn = "(X)"
if ps[0] in answers:
isIn = "(O)"
print "%s %s/%s/{%d,%d}/ %s" % (
isIn, ptnId, table[ptnId]["pattern"],
ps[1]["support"], ps[1]["total"], ps[0])
pass
# select top 1
break
# prevent second ans
break
def updateAnswer(jobid, inputPath, filename):
contenJson = projizz.jsonRead(os.path.join(inputPath, filename))
print "#%d - %s" % (jobid, filename)
connect = Connection()
answerCollection = connect.projizz.result.yago.answer
factCollection = connect.projizz.yago.facts
queries = map(lambda x: x[:-4], contenJson)
itr = answerCollection.find({"revid": {"$in": queries}})
print "#%d - query=%d,result=%d" % (jobid, len(queries), itr.count())
count = 0
ty1g = 0
ty2g = 0
updateC = 0
articles = []
for ans in itr:
count += 1
articleID = "%s.txt" % (ans["revid"])
articleName = ans["_id"]
properties = ans["properties"]
#not consider references.
#references = ans["references"]
if len(properties) == 0:
# give up those no properties' article
# print "#%d - give up %s (1)" % (jobid,articleID)
ty1g += 1
continue
needUpdate = len(properties)
lines = projizz.articleSimpleSentenceFileter(contenJson[articleID])
text = ""
for line in lines:
text += (line + " ")
observed = []
for pro in properties:
pitr = factCollection.find({
"property": pro,
"subject": articleName
})
if pitr.count() < 1:
notNeed.append(pro)
continue
found = False
for fact in pitr:
tokens = projizz.getNamedEntityTokens(fact["object"])
for token in tokens:
if token in text:
found = True
break
if found:
break
if found:
observed.append(pro)
if len(observed) > 0:
articles.append(articleID)
ans["observed"] = observed
answerCollection.update({"revid": ans["revid"]}, ans, upsert=False)
else:
ty2g += 1
#print "#%d - give up %s (2)" % (jobid,articleID)
print "#%d -> update %d (give up %d + %d)" % (jobid, len(articles), ty1g,
ty2g)
return (filename, articles)
def mapper(jobid, filename, inputPath, inputPtnPath, table, st, partAns, domainRange, confidence, nbcPath):
# read articles and patterns
contentJson = projizz.jsonRead(os.path.join(inputPath, filename))
contentPtnJson = projizz.jsonRead(os.path.join(inputPtnPath, filename))
classifiers = projizz.getNBClassifiers(nbcPath)
print "Worker %d : Read %s" % (jobid, filename)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid": {"$in": queries}})
print "worker %d query=%d, result=%d" % (jobid, len(queries), itr.count())
count = 0
expResult = partAns
relaEx = []
print "worker %d build expResult" % (jobid)
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
# targetName = ans["_id"].replace("(","").replace(")","").split("_") # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["observed"]
# origin properties, 理論上應該會比 observed 還要多
originRela = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
# Relation extraction
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
if lineText[0] == "^": # It's a wikipeida reference comments, ignore it!
continue
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
ptntks = table[ptnId]["pattern"]
if not projizz.isPatternValidate(ptnId, table, confidence=confidence, st=st):
continue
rfp = table[ptnId]["relations"]
# check degree
if len(rfp) > 5:
continue
# if no support, ignore this pattern
if st[ptnId][0][1]["support"] <= 0:
continue
for ptnst in st[ptnId]:
# ptnst[0] = relation
# ptnst[1] = {"support":,"total": }
if domainRange[ptnst[0]] not in types:
continue
if classifiers[ptnst[0]] == None:
continue
if classifiers[ptnst[0]].classify(lineText) == "pos":
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
#### Evaluation
for attribute in expResult:
# special case, ignore.
if attribute == "produced":
continue
postive = False
true = False
if attribute in relaEx:
postive = True
if attribute in relation:
true = True
if true:
if postive:
expResult[attribute]["tp"].append(ans["revid"])
else:
expResult[attribute]["fn"].append(ans["revid"])
else:
if postive:
expResult[attribute]["fp"].append(ans["revid"])
else:
# ignore true-negative
pass
if count % 100 == 0:
print "worker #%d done %d." % (jobid, count)
return expResult
def filterFunction(jobid, filename, inputPtnPath, model, table, partAns, st,
domainRange, inputPath, confidence):
# read patterns in articles
contentPtnJson = json.load(open(os.path.join(inputPtnPath, filename), "r"))
contentJson = projizz.jsonRead(os.path.join(inputPath, filename))
print "Worker %d : Read %s into filter" % (jobid, filename)
# connect to database
connect = pymongo.Connection()
db = connect.projizz
collection = db.result.yago.answer
queries = map(lambda x: x[:-4], contentPtnJson)
itr = collection.find({"revid": {"$in": queries}})
print "worker %d query=%d, result=%d" % (jobid, len(queries), itr.count())
count = 0
# prepare keys for multiple-exp
# degree: 1 ~ 5
# ambigu: select 1, select n (threshold:.5, .75), select all
# type or not: no type info, type info
expResult = {}
for deg in range(1, 6):
for typ in ["n", "t"]:
if not deg == 1:
for amb in ["one", "50", "75", "all"]:
keyname = "%d-%s-%s" % (deg, amb, typ)
expResult[keyname] = copy.deepcopy(partAns)
else:
keyname = "%d-1-%s" % (deg, typ)
expResult[keyname] = copy.deepcopy(partAns)
print "worker %d build expResult" % (jobid)
for ans in itr:
count += 1
key = "%s.txt" % (ans["revid"]) # get revid
#targetName = ans["_id"].replace("(","").replace(")","").split("_") # get entity name's part
types = ans["type"]
# Now only consider properties, no references.
relation = ans["observed"]
# origin properties, 理論上應該會比 observed 還要多
originRela = ans["properties"]
ptnEx = contentPtnJson[key]
article = projizz.articleSimpleSentenceFileter(contentJson[key])
for keyname in expResult:
args = keyname.split("-")
degree = int(args[0])
ambigu = args[1]
typ = args[2]
# Relation extraction
relaEx = []
for line in ptnEx:
# line[0]: line number
# line[1]: array of patterns
lineText = article[line[0]]
if lineText[
0] == "^": # It's a wikipeida reference comments, ignore it!
continue
for ptn in line[1]:
# ptn[0]: pattern ID
# ptn[1]: start position in line
# ptn[2]: end position in line
ptnId = "%d" % (ptn[0])
if not projizz.isPatternValidate(
ptnId, table, confidence=confidence, st=st):
continue
rfp = table[ptnId]["relations"]
# check degree
if len(rfp) > degree:
continue
if len(rfp) == 1: # or degree == 1
if st[ptnId][0][1]["support"] > 0 and not rfp[
0] in relaEx:
if typ == "t":
if domainRange[rfp[0]]["domain"] in types:
relaEx.append(rfp[0])
else:
relaEx.append(rfp[0])
else:
if ambigu == "one":
if typ == "t":
for ptnst in st[ptnId]:
# ptnst[0] = relation
# ptnst[1] = {"support": , "total": }
if ptnst[1]["support"] > 0 and domainRange[
ptnst[0]]["domain"] in types:
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
break
else:
if st[ptnId][0][1]["support"] > 0 and not rfp[
0] in relaEx:
relaEx.append(rfp[0])
elif ambigu == "all":
for ptnst in st[ptnId]:
if typ == "t":
if domainRange[
ptnst[0]]["domain"] in types:
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
else:
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
else:
th = 0.75
if ambigu == "50":
th = 0.5
b = st[ptnId][0][1]["support"]
if b > 0:
for ptnst in st[ptnId]:
if float(ptnst[1]["support"]) / float(
b) >= th:
if typ == "t":
if domainRange[ptnst[0]][
"domain"] in types and not ptnst[
0] in relaEx:
relaEx.append(ptnst[0])
else:
if not ptnst[0] in relaEx:
relaEx.append(ptnst[0])
# Evaluation
for attribute in expResult[keyname]:
# special case, ignore.
if attribute == "produced":
continue
postive = False
true = False
if attribute in relaEx:
postive = True
if attribute in relation:
true = True
if true:
if postive:
expResult[keyname][attribute]["tp"].append(
ans["revid"])
else:
expResult[keyname][attribute]["fn"].append(
ans["revid"])
else:
if postive:
expResult[keyname][attribute]["fp"].append(
ans["revid"])
else:
# ignore true-negative
pass
if count % 100 == 0:
print "worker #%d done %d." % (jobid, count)
return expResult