if split == True:
fout_split = []
for i in range(split_size):
fout_split[i] = open("clink.part" + str(i+1), 'w')
n = 0
feature_vectors = ""
for r, d, f in os.walk(dirpath):
for filename in f:
#print filename
#sys.stderr.write(filename + "\n")
if filename.endswith(".txp"):
filepath = os.path.join(r, filename)
input_file = open(filepath, 'r')
file_features = ff.FileFeatures(input_file.read(), filename, language, parser, inverse)
file_features.getFeatures()
if dirpath_csignal != "":
filepath_csignal = os.path.join(dirpath_csignal, filename+".csignals")
file_csignal = open(filepath_csignal, "r")
file_features.initCSignals(file_csignal.read())
file_csignal.close()
if dirpath_tlink != "":
filepath_tlink = os.path.join(dirpath_tlink, filename+".tlinks")
file_tlink = open(filepath_tlink, "r")
file_features.initTlinkPairs(file_tlink.read())
file_tlink.close()
if dirpath_clink != "":
filepath_clink = os.path.join(dirpath_clink, filename+".clinks")
file_clink = open(filepath_clink, "r")
file_features.initPairs(file_clink.read())
def getFeatureString(ff, e1, e2, morecs, csignal_para_dict):
feature_str = ""
(eidx1, tid1, _, eclass1, _, _) = ff.entities[e1]
(eidx2, tid2, _, eclass2, _, _) = ff.entities[e2]
(token1, sentid1, lemma1, pos1, mainvb1, entity1, chunk1, conn1, mainpos1, tense1, aspect1, pol1, supersense1) = ff.tokens[tid1]
(token2, sentid2, lemma2, pos2, mainvb2, entity2, chunk2, conn2, mainpos2, tense2, aspect2, pol2, supersense2) = ff.tokens[tid2]
(pos_path1, pos_pol1) = ff.getPOSPath(tid1) #get POS path (for verb, noun and adj are based on dependent verb) and polarity from POS
(pos_path2, pos_pol2) = ff.getPOSPath(tid2) #get POS path (for verb, noun and adj are based on dependent verb) and polarity from POS
(sent_distance, ent_distance, ent_order) = ff.getDistance(sentid1, sentid2, eidx1, eidx2)
if ent_order == "reverse":
(dep_rel, dep_order) = ff.getDependency(tid2, tid1)
(dep_path, path_order) = ff.getDependencyPath(tid2, tid1)
else:
(dep_rel, dep_order) = ff.getDependency(tid1, tid2)
(dep_path, path_order) = ff.getDependencyPath(tid1, tid2)
samePOS = (pos1 == pos2)
sameClass = (eclass1 == eclass2)
sameTense = (tense1 == tense2)
sameAspect = (aspect1 == aspect2)
samePol = (pol1 == pol2)
#(marker, marker_position, dep_mark_e1, dep_mark_e2) = (["O"],"O","O","O")
(marker, marker_position, dep_mark_e1, dep_mark_e2) = ([],"O","O","O")
if ent_order == "reverse": (causal_signal, causal_signal_pos, dep_signal_e1, dep_signal_e2) = ff.getCausalSignal(e2, e1)
else: (causal_signal, causal_signal_pos, dep_signal_e1, dep_signal_e2) = ff.getCausalSignal(e1, e2)
if causal_signal != "O":
causal_signals = []
if morecs and ((e1, e2) in ff.clink or (e2, e1) in ff.clink):
for cs in __getParaphraseCausalSignal(causal_signal, csignal_para_dict):
causal_signals.append(cs)
causal_signals.append(causal_signal)
(marker, marker_position, dep_mark_e1, dep_mark_e2) = (causal_signals, causal_signal_pos, dep_signal_e1, dep_signal_e2)
else:
if ent_order == "reverse": (causal_conn, causal_conn_pos, dep_conn_e1, dep_conn_e2) = ff.getCausalConnective(e2, e1)
else: (causal_conn, causal_conn_pos, dep_conn_e1, dep_conn_e2) = ff.getCausalConnective(e1, e2)
if causal_conn != "O":
causal_conns = []
causal_conns.append(causal_conn)
(marker, marker_position, dep_mark_e1, dep_mark_e2) = (causal_conns, causal_conn_pos, dep_conn_e1, dep_conn_e2)
else:
if ent_order == "reverse": (causal_verb, dep_e1, dep_e2) = ff.getCausativeVerb(e2, e1)
else: (causal_verb, dep_e1, dep_e2) = ff.getCausativeVerb(e1, e2)
if causal_verb != "O":
causal_verbs = []
causal_verbs.append(causal_verb)
(marker, marker_position, dep_mark_e1, dep_mark_e2) = (causal_verbs, "BETWEEN", dep_e1, dep_e2)
(csignal_e1, csignal_pos_e1) = ff.getCSignalDependency(e1)
(csignal_e2, csignal_pos_e2) = ff.getCSignalDependency(e2)
(cverb_e1, cverb_pos_e1) = ff.getCVerbDependency(e1)
(cverb_e2, cverb_pos_e2) = ff.getCVerbDependency(e2)
coref = "O"
if (e1, e2) in ff.coref_events or (e2, e1) in ff.coref_events: coref = "COREF"
tlink = "O"
if ent_order == "reverse":
if (e2, e1) in ff.tlink and ff.tlink[(e2, e1)] != "NONE": tlink = ff.tlink[(e2, e1)]
elif (e1, e2) in ff.tlink and ff.tlink[(e1, e2)] != "NONE": tlink = ff.getInverseRelation(ff.tlink[(e1, e2)])
else: tlink = "O"
else:
if (e1, e2) in ff.tlink and ff.tlink[(e1, e2)] != "NONE": tlink = ff.tlink[(e1, e2)]
elif (e2, e1) in ff.tlink and ff.tlink[(e2, e1)] != "NONE": tlink = ff.getInverseRelation(ff.tlink[(e2, e1)])
else: tlink = "O"
conceptnet = "O"
#if ent_order == "reverse":
# conceptnet = __getConceptRel(lemma2, lemma1)
#else:
# conceptnet = __getConceptRel(lemma1, lemma2)
pair_str = ""
feature_strings = ""
for m in marker:
feature_str = ""
if ent_order == "reverse":
feature_str += "%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % \
(e2, e1, token2, token1, lemma2, lemma1, mainpos2+"-"+mainpos1, chunk2+"-"+chunk1, sent_distance, ent_distance, conceptnet, dep_rel, dep_order, dep_path, path_order, str(mainvb2)+"-"+str(mainvb1), eclass2+"-"+eclass1, tense2+"-"+tense1, aspect2+"-"+aspect1, pol2+"-"+pol1, samePOS, sameClass, sameTense, sameAspect, samePol, pos_path2+"-"+pos_path1, pos_pol2+"-"+pos_pol1, m, marker_position, dep_mark_e1, dep_mark_e2, csignal_e2, csignal_pos_e2, csignal_e1, csignal_pos_e1, cverb_e2, cverb_pos_e2, cverb_e1, cverb_pos_e1, tlink, coref, supersense2, supersense1, entity2, entity1)
else:
feature_str += "%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % \
(e1, e2, token1, token2, lemma1, lemma2, mainpos1+"-"+mainpos2, chunk1+"-"+chunk2, sent_distance, ent_distance, conceptnet, dep_rel, dep_order, dep_path, path_order, str(mainvb1)+"-"+str(mainvb2), eclass1+"-"+eclass2, tense1+"-"+tense2, aspect1+"-"+aspect2, pol1+"-"+pol2, samePOS, sameClass, sameTense, sameAspect, samePol, pos_path1+"-"+pos_path2, pos_pol1+"-"+pos_pol2, m, marker_position, dep_mark_e1, dep_mark_e2, csignal_e1, csignal_pos_e1, csignal_e2, csignal_pos_e2, cverb_e1, cverb_pos_e1, cverb_e2, cverb_pos_e2, tlink, coref, supersense1, supersense2, entity1, entity2)
#clink
clink = "O"
if ent_order == "reverse":
if (e2, e1) in ff.clink: clink = "CLINK"
elif (e1, e2) in ff.clink: clink = "CLINK-R"
else: clink = "O"
else:
if (e1, e2) in ff.clink: clink = "CLINK"
elif (e2, e1) in ff.clink: clink = "CLINK-R"
else: clink = "O"
feature_strings += feature_str + "\t" + clink + "\n"
return feature_strings
def buildPairFeatures(ff, pair_type, classification, et_opt, ee_opt):
event_event_str = ""
event_timex_str = ""
timex_timex_str = ""
event_timex_dct = ""
event_timex_non_dct = ""
event_timex_main = ""
event_event_main = ""
n_ee_pairs = 0
n_et_pairs = 0
n_tt_pairs = 0
for (e1, e2) in ff.tlink:
#print e1, e2, ff.tlink[(e1, e2)]
if e1 in ff.entities and e2 in ff.entities:
if ff.isTimex(e1):
(eidx1, tid_start1, tid_end1, timex_type1, timex_value1,
dct1) = ff.entities[e1]
if dct1: sentid1 = "O"
else:
(_, sentid1, _, _, _, _, _, _, _, _, _, _,
_) = ff.tokens[tid_start1]
(lemma1, token1) = ff.getLemmaTokenTimex(e1)
if ff.isTimex(e2): #timex-timex pair
#(eidx2, tid_start2, tid_end2, timex_type2, timex_value2, dct2) = ff.entities[e2]
#if dct2: sentid2 = "O"
#else: (_, sentid2, _, _, _, _, _, _, _, _, _, _, _) = ff.tokens[tid_start2]
#(lemma2, token2) = ff.getLemmaTokenTimex(e2)
#(sent_distance, ent_distance, ent_order) = ff.getDistance(sentid1, sentid2, eidx1, eidx2)
#(temp_conn1, temp_conn_pos1) = ff.getTemporalConnective(e1)
#(temp_conn2, temp_conn_pos2) = ff.getTemporalConnective(e2)
#(temp_signal1, temp_signal_pos1) = ff.getTemporalSignal(e1)
#(temp_signal2, temp_signal_pos2) = ff.getTemporalSignal(e2)
#tt_str = "%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % \
# (e1, e2, token1, token2, sent_distance, ent_distance, ent_order, timex_type1+"-"+timex_type2, timex_value1+"-"+timex_value2, dct1, dct2, temp_signal1, temp_signal_pos1, temp_signal2, temp_signal_pos2, temp_conn1, temp_conn_pos1, temp_conn2, temp_conn_pos2)
#if classification == "bin":
# if ff.tlink[(e1, e2)] != "NONE": rel_type = "REL"
# else: rel_type = ff.tlink[(e1, e2)]
# timex_timex_str += tt_str + "\t%s\n" % rel_type
#elif classification == "rel":
# if ff.tlink[(e1, e2)] != "NONE": timex_timex_str += tt_str + "\t%s\n" % ff.tlink[(e1, e2)]
#else: timex_timex_str += tt_str + "\t%s\n" % ff.tlink[(e1, e2)]
#n_tt_pairs += 1
#if n_tt_pairs % 25 == 0: timex_timex_str += "\n"
pass
else: #timex-event pair
pair_order = "te"
(eidx2, tid2, _, eclass2, _, _) = ff.entities[e2]
(token2, sentid2, lemma2, pos2, mainvb2, entity2, chunk2,
conn2, mainpos2, tense2, aspect2, pol2,
supersense2) = ff.tokens[tid2]
(pos_path2, pos_pol2) = ff.getPOSPath(
tid2
) #get POS path (for verb, noun and adj are based on dependent verb) and polarity from POS
(dep_rel, dep_order) = ("O", "O")
(dep_path, path_order) = ("O", "O")
if not dct1:
for i in range(int(tid_start1), int(tid_end1) + 1):
(dep_rel,
dep_order) = ff.getDependency(tid2, str(i))
if dep_rel != "O": break
(dep_path,
path_order) = ff.getDependencyPath(tid2, str(i))
if dep_path != "O": break
(sent_distance, ent_distance,
ent_order) = ff.getDistance(sentid1, sentid2, eidx1,
eidx2)
(temp_conn1, temp_conn_pos1) = ff.getTemporalConnective(e2)
(temp_conn2, temp_conn_pos2) = ff.getTemporalConnective(e1)
(temp_signal1, temp_signal_pos1) = ff.getTemporalSignal(e2)
(temp_signal2, temp_signal_pos2) = ff.getTemporalSignal(e1)
timex_rule = ff.getTimexRule(e1)
reltype_rule = ff.getRelTypeRule(temp_signal2, pair_order,
eclass2, timex_type1,
timex_value1, e1)
et_str = ""
et_str += "%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % \
(e2, e1, pair_order, token2, token1, lemma2, lemma1, mainpos2, chunk2, sent_distance, ent_distance, ent_order, dep_rel, dep_order, dep_path, path_order, mainvb2, eclass2, tense2, aspect2, pol2, timex_type1, timex_value1, dct1, pos_path2, pos_pol2, temp_signal2, temp_signal_pos2, temp_signal1, temp_signal_pos1, temp_conn2, temp_conn_pos2, temp_conn1, temp_conn_pos1, timex_rule)
if classification == "bin":
if ff.tlink[(e1, e2)] != "NONE": rel_type = "REL"
else: rel_type = ff.tlink[(e1, e2)]
et_str += "\t%s" % rel_type
if et_opt == "dct" and dct1:
event_timex_dct += et_str + "\tREL\n"
elif et_opt == "non-dct" and not dct1:
event_timex_non_dct += et_str + "\tREL\n"
elif et_opt == "dct-main" and dct1:
if mainvb2: event_timex_dct += et_str + "\tREL\n"
else: event_timex_str += et_str + "\n"
elif et_opt == "main":
if mainvb2: event_timex_main += et_str + "\tREL\n"
else: event_timex_str += et_str + "\n"
elif et_opt == "rule":
if reltype_rule != "O":
event_timex_main += et_str + "\t" + reltype_rule + "\n"
else:
event_timex_str += et_str + "\n"
else:
event_timex_str += et_str + "\n"
elif classification == "rel":
if True:
#if ff.tlink[(e1, e2)] != "NONE":
#if ff.tlink[(e1, e2)] != "NONE" and ff.tlink[(e1, e2)] != "ENDED_BY" and ff.tlink[(e1, e2)] != "BEGUN_BY":
#for QA-TempEval: DURING and IDENTITY are mapped to SIMULTANEOUS, IBEFORE/IAFTER are mapped to BEFORE/AFTER
# BEGUN_BY, ENDED_BY and INCLUDES are mapped to BEGINS, ENDS and IS_INCLUDED
rel_type = ff.getInverseRelation2(ff.tlink[(e1,
e2)])
#if rel_type == "DURING" or rel_type == "DURING_INV" or rel_type == "IDENTITY": et_str += "\t%s" % "SIMULTANEOUS"
if rel_type == "IBEFORE":
et_str += "\t%s" % "BEFORE"
elif rel_type == "IAFTER":
et_str += "\t%s" % "AFTER"
elif rel_type == "BEGINS" or rel_type == "ENDS" or rel_type == "INCLUDES":
et_str += "\t%s" % ff.getInverseRelation(
ff.tlink[(e1, e2)])
elif rel_type == "IS_INCLUDED" and timex_type1 == "DURATION":
et_str += "\t%s" % "MEASURE" #for NewsReader
else:
et_str += "\t%s" % rel_type
#et_str += "\t%s" % ff.tlink[(e1, e2)]
if et_opt == "rule":
if reltype_rule != "O" and sent_distance == 0:
event_timex_main += et_str + "\t" + reltype_rule + "\n"
else:
event_timex_str += et_str + "\n"
else:
event_timex_str += et_str + "\n"
else:
event_timex_str += et_str + "\t%s\n" % ff.tlink[
(e1, e2)]
n_et_pairs += 1
#if n_et_pairs % 25 == 0: event_timex_str += "\n"
else:
(eidx1, tid1, _, eclass1, _, _) = ff.entities[e1]
(token1, sentid1, lemma1, pos1, mainvb1, entity1, chunk1,
conn1, mainpos1, tense1, aspect1, pol1,
supersense1) = ff.tokens[tid1]
(pos_path1, pos_pol1) = ff.getPOSPath(
tid1
) #get POS path (for verb, noun and adj are based on dependent verb) and polarity from POS
if ff.isTimex(e2): #event-timex pair
pair_order = "et"
(eidx2, tid_start2, tid_end2, timex_type2, timex_value2,
dct2) = ff.entities[e2]
if dct2: sentid2 = "O"
else:
(_, sentid2, _, _, _, _, _, _, _, _, _, _,
_) = ff.tokens[tid_start2]
(lemma2, token2) = ff.getLemmaTokenTimex(e2)
(dep_rel, dep_order) = ("O", "O")
(dep_path, path_order) = ("O", "O")
if not dct2:
for i in range(int(tid_start2), int(tid_end2) + 1):
(dep_rel,
dep_order) = ff.getDependency(tid1, str(i))
if dep_rel != "O": break
(dep_path,
path_order) = ff.getDependencyPath(tid1, str(i))
if dep_path != "O": break
(sent_distance, ent_distance,
ent_order) = ff.getDistance(sentid1, sentid2, eidx1,
eidx2)
(temp_signal1, temp_signal_pos1) = ff.getTemporalSignal(e1)
(temp_signal2, temp_signal_pos2) = ff.getTemporalSignal(e2)
(temp_conn1, temp_conn_pos1) = ff.getTemporalConnective(e1)
(temp_conn2, temp_conn_pos2) = ff.getTemporalConnective(e2)
timex_rule = ff.getTimexRule(e2)
reltype_rule = ff.getRelTypeRule(temp_signal2, pair_order,
eclass1, timex_type2,
timex_value2, e2)
et_str = ""
et_str += "%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % \
(e1, e2, pair_order, token1, token2, lemma1, lemma2, mainpos1, chunk1, sent_distance, ent_distance, ent_order, dep_rel, dep_order, dep_path, path_order, mainvb1, eclass1, tense1, aspect1, pol1, timex_type2, timex_value2, dct2, pos_path1, pos_pol1, temp_signal1, temp_signal_pos1, temp_signal2, temp_signal_pos2, temp_conn1, temp_conn_pos1, temp_conn2, temp_conn_pos2, timex_rule)
if classification == "bin":
if ff.tlink[(e1, e2)] != "NONE": rel_type = "REL"
else: rel_type = ff.tlink[(e1, e2)]
et_str += "\t%s" % rel_type
if et_opt == "dct" and dct2:
event_timex_dct += et_str + "\tREL\n"
elif et_opt == "non-dct" and not dct2:
event_timex_non_dct += et_str + "\tREL\n"
elif et_opt == "dct-main" and dct2:
if mainvb1: event_timex_dct += et_str + "\tREL\n"
else: event_timex_str += et_str + "\n"
elif et_opt == "main":
if mainvb1: event_timex_main += et_str + "\tREL\n"
else: event_timex_str += et_str + "\n"
elif et_opt == "rule":
if reltype_rule != "O":
event_timex_main += et_str + "\t" + reltype_rule + "\n"
else:
event_timex_str += et_str + "\n"
else:
event_timex_str += et_str + "\n"
elif classification == "rel":
if True:
#if ff.tlink[(e1, e2)] != "NONE":
#if ff.tlink[(e1, e2)] != "NONE" and ff.tlink[(e1, e2)] != "ENDED_BY" and ff.tlink[(e1, e2)] != "BEGUN_BY":
#for QA-TempEval: DURING and IDENTITY are mapped to SIMULTANEOUS, IBEFORE/IAFTER are mapped to BEFORE/AFTER
# BEGUN_BY, ENDED_BY and INCLUDES are mapped to BEGINS, ENDS and IS_INCLUDED
rel_type = ff.tlink[(e1, e2)]
#if rel_type == "DURING" or rel_type == "DURING_INV" or rel_type == "IDENTITY": et_str += "\t%s" % "SIMULTANEOUS"
if rel_type == "IBEFORE":
et_str += "\t%s" % "BEFORE"
elif rel_type == "IAFTER":
et_str += "\t%s" % "AFTER"
elif rel_type == "BEGINS" or rel_type == "ENDS" or rel_type == "INCLUDES":
et_str += "\t%s" % ff.getInverseRelation(
ff.tlink[(e1, e2)])
elif rel_type == "IS_INCLUDED" and timex_type2 == "DURATION":
et_str += "\t%s" % "MEASURE" #for NewsReader
else:
et_str += "\t%s" % rel_type
#et_str += "\t%s" % ff.tlink[(e1, e2)]
if et_opt == "rule":
if reltype_rule != "O" and sent_distance == 0:
event_timex_main += et_str + "\t" + reltype_rule + "\n"
else:
event_timex_str += et_str + "\n"
else:
event_timex_str += et_str + "\n"
else:
event_timex_str += et_str + "\t%s\n" % ff.tlink[
(e1, e2)]
n_et_pairs += 1
#if n_et_pairs % 25 == 0: event_timex_str += "\n"
else: #event-event pair
(eidx2, tid2, _, eclass2, _, _) = ff.entities[e2]
(token2, sentid2, lemma2, pos2, mainvb2, entity2, chunk2,
conn2, mainpos2, tense2, aspect2, pol2,
supersense2) = ff.tokens[tid2]
(pos_path2, pos_pol2) = ff.getPOSPath(
tid2
) #get POS path (for verb, noun and adj are based on dependent verb) and polarity from POS
(sent_distance, ent_distance,
ent_order) = ff.getDistance(sentid1, sentid2, eidx1,
eidx2)
if ent_order == "reverse":
(dep_rel, dep_order) = ff.getDependency(tid2, tid1)
(dep_path,
path_order) = ff.getDependencyPath(tid2, tid1)
else:
(dep_rel, dep_order) = ff.getDependency(tid1, tid2)
(dep_path,
path_order) = ff.getDependencyPath(tid1, tid2)
samePOS = (pos1 == pos2)
sameClass = (eclass1 == eclass2)
sameTense = (tense1 == tense2)
sameAspect = (aspect1 == aspect2)
samePol = (pol1 == pol2)
(temp_conn1, temp_conn_pos1) = ff.getTemporalConnective(e1)
(temp_conn2, temp_conn_pos2) = ff.getTemporalConnective(e2)
(temp_signal1, temp_signal_pos1) = ff.getTemporalSignal(e1)
(temp_signal2, temp_signal_pos2) = ff.getTemporalSignal(e2)
if ent_order == "reverse":
if (e2, e1) in ff.clink: clink = ff.clink[(e2, e1)]
else: clink = "O"
else:
if (e1, e2) in ff.clink: clink = ff.clink[(e1, e2)]
else: clink = "O"
coref = "O"
if (e1, e2) in ff.coref_events or (e2,
e1) in ff.coref_events:
coref = "COREF"
ee_str = ""
if ent_order == "reverse":
ee_str += "%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % \
(e2, e1, token2, token1, lemma2, lemma1, mainpos2+"-"+mainpos1, chunk2+"-"+chunk1, sent_distance, ent_distance, ent_order, dep_rel, dep_order, dep_path, path_order, str(mainvb2)+"-"+str(mainvb1), eclass2+"-"+eclass1, tense2+"-"+tense1, aspect2+"-"+aspect1, pol2+"-"+pol1, samePOS, sameClass, sameTense, sameAspect, samePol, pos_path2+"-"+pos_path1, pos_pol2+"-"+pos_pol1, temp_signal2, temp_signal_pos2, temp_signal1, temp_signal_pos1, temp_conn2, temp_conn_pos2, temp_conn1, temp_conn_pos1, clink, coref)
else:
ee_str += "%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % \
(e1, e2, token1, token2, lemma1, lemma2, mainpos1+"-"+mainpos2, chunk1+"-"+chunk2, sent_distance, ent_distance, ent_order, dep_rel, dep_order, dep_path, path_order, str(mainvb1)+"-"+str(mainvb2), eclass1+"-"+eclass2, tense1+"-"+tense2, aspect1+"-"+aspect2, pol1+"-"+pol2, samePOS, sameClass, sameTense, sameAspect, samePol, pos_path1+"-"+pos_path2, pos_pol1+"-"+pos_pol2, temp_signal1, temp_signal_pos1, temp_signal2, temp_signal_pos2, temp_conn1, temp_conn_pos1, temp_conn2, temp_conn_pos2, clink, coref)
if classification == "bin":
if ff.tlink[(e1, e2)] != "NONE": rel_type = "REL"
else: rel_type = ff.tlink[(e1, e2)]
ee_str += "\t%s" % rel_type
if ee_opt == "main":
if mainvb1 or mainvb2:
event_event_main += ee_str + "\tREL\n"
else:
event_event_str += ee_str + "\n"
elif ee_opt == "coref":
if coref == "COREF":
event_event_main += ee_str + "\tSIMULTANEOUS\n" #NewsReader and QA-TempEval no IDENTITY
#if coref == "COREF": event_event_main += ee_str + "\tIDENTITY\n"
else:
event_event_str += ee_str + "\n"
else:
event_event_str += ee_str + "\n"
elif classification == "rel":
if True:
#if ff.tlink[(e1, e2)] != "NONE":
#if ff.tlink[(e1, e2)] != "NONE" and ff.tlink[(e1, e2)] != "BEGINS" and ff.tlink[(e1, e2)] != "BEGUN_BY" and ff.tlink[(e1, e2)] != "ENDS" and ff.tlink[(e1, e2)] != "ENDED_BY" and ff.tlink[(e1, e2)] != "IAFTER" and ff.tlink[(e1, e2)] != "IBEFORE":
#for QA-TempEval: DURING and IDENTITY are mapped to SIMULTANEOUS, IBEFORE/IAFTER are mapped to BEFORE/AFTER
rel_type = ff.tlink[(e1, e2)]
if ent_order == "reverse":
rel_type = ff.getInverseRelation2(rel_type)
#if rel_type == "DURING" or rel_type == "DURING_INV" or rel_type == "IDENTITY": ee_str += "\t%s" % "SIMULTANEOUS"
if rel_type == "IBEFORE":
ee_str += "\t%s" % "BEFORE"
elif rel_type == "IAFTER":
ee_str += "\t%s" % "AFTER"
else:
ee_str += "\t%s" % rel_type
#event_event_str += ee_str + "\t%s\n" % ff.tlink[(e1, e2)]
if ee_opt == "coref":
if coref == "COREF":
event_event_main += ee_str + "\tSIMULTANEOUS\n" #NewsReader and QA-TempEval no IDENTITY
#if coref == "COREF": event_event_main += ee_str + "\tIDENTITY\n"
else:
event_event_str += ee_str + "\n"
else:
event_event_str += ee_str + "\n"
else:
event_event_str += ee_str + "\t%s\n" % ff.tlink[
(e1, e2)]
n_ee_pairs += 1
#if n_ee_pairs % 25 == 0: event_event_str += "\n"
for (e1, e2) in ff.tmxlink:
timex_timex_str += e1 + "\t" + e2 + "\t" + ff.tmxlink[(e1, e2)] + "\n"
#print event_event_str
#print event_timex_str
#print timex_timex_str
if pair_type == "ee":
if ee_opt == "main": return (event_event_main, event_event_str)
elif ee_opt == "coref":
#the rest of the corefer-events not in tlinks? label them as SIMULTANEOUS?
for (coev1, coev2) in ff.coref_events:
if (coev1, coev2) not in ff.tlink and (coev2,
coev1) not in ff.tlink:
print coev1 + "\t" + coev2 + "\tSIMULTANEOUS" #NewsReader and QA-TempEval no IDENTITY
#print coev1 + "\t" + coev2 + "\tIDENTITY"
return (event_event_main, event_event_str)
else:
return event_event_str
elif pair_type == "et":
if et_opt == "dct": return (event_timex_dct, event_timex_str)
elif et_opt == "non-dct": return (event_timex_non_dct, event_timex_str)
elif et_opt == "dct-main": return (event_timex_dct, event_timex_str)
elif et_opt == "main": return (event_timex_main, event_timex_str)
elif et_opt == "rule": return (event_timex_main, event_timex_str)
else: return event_timex_str
elif pair_type == "tt": return timex_timex_str
