def handle_candidate(self, reference, info={}):
"""For each entry in the reference Gold Standard, store it in main memory
in the `pre_gs` global list.
@param reference A `Pattern` contained in the reference Gold Standard.
"""
global ignore_pos
global ref_counter
global ignore_case
global pre_gs
global lemma_or_surface
global fuzzy_pre_gs
if ignore_pos :
reference.set_all( pos=WILDCARD ) # reference has type Pattern
pre_gs_key = reference.to_string()
if ignore_case :
pre_gs_key = pre_gs_key.lower()
pre_gs_entry = pre_gs.get( pre_gs_key, [] )
pre_gs_entry.append( reference )
pre_gs[ pre_gs_key ] = pre_gs_entry
if lemma_or_surface:
fuzzy_pre_gs.setdefault(WORD_SEPARATOR.join(
[w.lemma for w in reference]), []).append(reference)
fuzzy_pre_gs.setdefault(WORD_SEPARATOR.join(
[w.surface for w in reference]), []).append(reference)
#gs.append( reference )
ref_counter = ref_counter + 1
def handle_candidate(self, reference, info={}):
"""For each entry in the reference Gold Standard, store it in main memory
in the `pre_gs` global list.
@param reference A `Pattern` contained in the reference Gold Standard.
"""
global ignore_pos
global ref_counter
global ignore_case
global pre_gs
global lemma_or_surface
global fuzzy_pre_gs
if ignore_pos:
reference.set_all(pos=WILDCARD) # reference has type Pattern
pre_gs_key = reference.to_string()
if ignore_case:
pre_gs_key = pre_gs_key.lower()
pre_gs_entry = pre_gs.get(pre_gs_key, [])
pre_gs_entry.append(reference)
pre_gs[pre_gs_key] = pre_gs_entry
if lemma_or_surface:
fuzzy_pre_gs.setdefault(
WORD_SEPARATOR.join([w.lemma for w in reference]),
[]).append(reference)
fuzzy_pre_gs.setdefault(
WORD_SEPARATOR.join([w.surface for w in reference]),
[]).append(reference)
#gs.append( reference )
ref_counter = ref_counter + 1
def handle_candidate(self, candidate_i, info={}):
"""For each candidate, verifies whether it is contained in the reference
list (in which case it is a *True* positive) or else, it is not in the
reference list (in which case it is a *False* positive, i.e. a random
ngram that does not constitute a MWE).
@param candidate_i The `Candidate` that is being read from the XML file.
"""
global ignore_pos
global gs_name
global ignore_case
global entity_counter
global tp_counter
global pre_gs
global lemma_or_surface
global fuzzy_pre_gs
true_positive = False
#pdb.set_trace()
candidate = self.candidate_factory.make()
for w in candidate_i:
copy_w = Word(w.surface, w.lemma, w.pos, w.syn)
candidate.append(copy_w)
if ignore_pos:
candidate.set_all(pos=WILDCARD) # reference has type Pattern
pre_gs_key = candidate.to_string()
if ignore_case:
pre_gs_key = pre_gs_key.lower()
entries_to_check = pre_gs.get(pre_gs_key, [])
if lemma_or_surface:
entries_to_check += fuzzy_pre_gs.get(
WORD_SEPARATOR.join([w.lemma for w in candidate]), [])
entries_to_check += fuzzy_pre_gs.get(
WORD_SEPARATOR.join([w.surface for w in candidate]), [])
for gold_entry in entries_to_check:
if gold_entry.match(candidate,
ignore_case=ignore_case,
lemma_or_surface=lemma_or_surface):
true_positive = True
break # Stop at first positive match
if true_positive:
candidate_i.add_tpclass(TPClass(gs_name, "True"))
tp_counter = tp_counter + 1
else:
candidate_i.add_tpclass(TPClass(gs_name, "False"))
self.chain.handle_candidate(candidate_i, info)
entity_counter += 1
def handle_candidate(self, candidate_i, info={}) :
"""For each candidate, verifies whether it is contained in the reference
list (in which case it is a *True* positive) or else, it is not in the
reference list (in which case it is a *False* positive, i.e. a random
ngram that does not constitute a MWE).
@param candidate_i The `Candidate` that is being read from the XML file.
"""
global ignore_pos
global gs_name
global ignore_case
global entity_counter
global tp_counter
global pre_gs
global lemma_or_surface
global fuzzy_pre_gs
true_positive = False
#pdb.set_trace()
candidate = self.candidate_factory.make()
for w in candidate_i :
copy_w = Word( w.surface, w.lemma, w.pos, w.syn)
candidate.append( copy_w )
if ignore_pos :
candidate.set_all( pos=WILDCARD ) # reference has type Pattern
pre_gs_key = candidate.to_string()
if ignore_case :
pre_gs_key = pre_gs_key.lower()
entries_to_check = pre_gs.get( pre_gs_key, [] )
if lemma_or_surface:
entries_to_check += fuzzy_pre_gs.get(WORD_SEPARATOR.join([w.lemma for w in candidate]), [])
entries_to_check += fuzzy_pre_gs.get(WORD_SEPARATOR.join([w.surface for w in candidate]), [])
for gold_entry in entries_to_check :
if gold_entry.match( candidate, ignore_case=ignore_case, lemma_or_surface=lemma_or_surface ) :
true_positive = True
break # Stop at first positive match
if true_positive :
candidate_i.add_tpclass( TPClass( gs_name, "True" ) )
tp_counter = tp_counter + 1
else :
candidate_i.add_tpclass( TPClass( gs_name, "False" ) )
self.chain.handle_candidate(candidate_i, info)
entity_counter += 1
def key(ngram):
"""
Returns a string key for the given list of words (strings).
(Shelves can only be indexed by strings and integers.)
"""
return WORD_SEPARATOR.join(ngram)
def key(ngram):
"""
Returns a string key for the given list of words (strings).
(Shelves can only be indexed by strings and integers.)
"""
return WORD_SEPARATOR.join(ngram)