def equals_cross_reference(sense):
xr = sense.equals_crossreference()
target_senses, sense_count = tdb.cross_reference_target(lemma=xr.lemma,
refentry=xr.refentry, refid=xr.refid, wordclass=sense.wordclass)
if target_senses:
hiscores = [t for t in target_senses
if t.rating() == target_senses[0].rating()]
hiscores.sort(key=lambda i: i.node_size(), reverse=True)
if hiscores[0].thesclass is not None:
match = hiscores[0].thesclass
match.reason_text = 'Equivalent to %s' % hiscores[0].lemma
match.reason_code = 'eqxr'
return match
return None
def cf_cross_reference(sense):
"""
If the current sense has 'cf'-type cross-reference, the classification
of the target sense is taken as a good guide to the classification
of the current sense.
If the target sense and the current sense are in the same wordclass and
have the same end word-ending, we assume that the current sense should
go in the target sense's class (similar to how 'equals'-type xrefs are
treated.
Otherwise, we put the current sense at the top of the equivalent
wordclass-level branch.
"""
xr = sense.cf_crossreference()
# Nb don't specify a wordclass here, since the target wordclass may well
# be different from the current sense's wordclass
target_senses, sense_count = tdb.cross_reference_target(lemma=xr.lemma,
refentry=xr.refentry, refid=xr.refid)
# Don't attempt if the target is too ambiguous (too many possible senses)
if target_senses and sense_count <= 3:
high_scores = [t for t in target_senses
if t.rating() == target_senses[0].rating()]
high_scores.sort(key=lambda i: i.node_size(), reverse=True)
if high_scores[0].thesclass is not None:
target = high_scores[0]
if (target.wordclass == sense.wordclass and
target.lemma[-2:] == sense.lemma[-2:]):
match = target.thesclass
elif target.wordclass == sense.wordclass:
match = target.wordclass_parent()
else:
match = tdb.equivalent_class(target.thesclass, sense.wordclass)
if match is not None:
match.reason_text = 'Analogy with target of cf-type xref ("%s")' % target.lemma
match.reason_code = 'cfxr'
return match
return None