def add_morph(original, new):
"""
Adds the original morphological analysis to the replacing words.
>>> add_morph([(u'les', u'DET'), (u'petites', u'JJ'), (u'filles', u'NN')],\\
... [(u'les', u'DET'), (u'mignon', u'JJ'), (u'chat', u'NN')])
([u'^le<det><def><mf><pl>$', u'^mignon<adj><f><pl>$', \
u'^chat<n><m><pl>$'], \
[(u'mignon', u'JJ'), (u'chat', u'NN')])
:param original: list of the original words with their POS tags as tuples
:param new: tuple list of the words of the new poem with their POS tags
:return: a tuple with a list of the lemmas of the new poem with
the morphological rules for the word form generation
('^word<tag1><tag2>...$'), and
a tuple list of the words used in the replacement
with their POS tags
"""
string_orig = ''
string_new = ''
analysis = []
new_words = []
if len(original) == len(new):
for i in range(len(original)):
string_orig = string_orig + original[i][0] + ' '
string_new = string_new + new[i][0] + ' '
morph_orig = morpha_fr.analyse_morphologically(string_orig,
output='list')
morph_new = morpha_fr.analyse_morphologically(string_new,
output='list')
if len(morph_orig) == len(morph_new):
for i in range(len(morph_orig)):
pos = original[i][1]
block_list = [u'avoir', #have
u'être', #be
u'aller', #go
u'venir', #come
u'faire', #do
u'vouloir']#want
block = False
for b in block_list:
if morph_orig[i].lower().find(b) != -1:
block = True
if block:
new_word = re.sub(ur'\^(.*?)/.*', '\g<1>', morph_orig[i])
elif morph_orig[i] != morph_new[i]:
(new_word, is_new) = find_correct_analysis(morph_new[i],
morph_orig[i],
pos)
if is_new:
new_words.append(new[i])
else:
(new_word, is_new) = find_correct_analysis(morph_orig[i],
morph_orig[i],
pos)
analysis.append(new_word)
return (analysis, new_words)
def tag_with_apertium(text, tagger='pos_tag_melt'):
"""
Uses Apertium to tokenize the words and tagger to tag the tokens.
>>> tag_with_apertium(u'ses beaux cheveux')
[u'ses_DET', u'beaux_JJ', u'cheveux_NN']
:param text: string of words
:param tagger: method to use for POS-tagging
:return: list of tagged words with an underscore separating
the word and the tag
"""
analysed = morpha_fr.analyse_morphologically(text, output='list')
string = ''
for a in analysed:
word = re.sub(ur'\^(.*?)/.*', '\g<1>', a)
string = string + word + ' $ '
# Use the function given in the tagger variable
tag = getattr(tag_fr, tagger)
try:
tagged = tag(string)
# Use the Stanford tagger if MElt is not installed.
except OSError:
tagged = pos_tag_stanford(string)
tagged = re.sub(ur'\$_.*? ', '$ ', tagged)
words = tagged.split('$')
trimmed = []
for w in words:
w = w.strip()
if w != '':
trimmed.append(w)
return trimmed
def tag_with_apertium(text, tagger='pos_tag_melt'):
"""
Uses Apertium to tokenize the words and tagger to tag the tokens.
>>> tag_with_apertium(u'ses beaux cheveux')
[u'ses_DET', u'beaux_JJ', u'cheveux_NN']
:param text: string of words
:param tagger: method to use for POS-tagging
:return: list of tagged words with an underscore separating
the word and the tag
"""
analysed = morpha_fr.analyse_morphologically(text, output='list')
string = ''
for a in analysed:
word = re.sub(ur'\^(.*?)/.*', '\g<1>', a)
string = string + word + ' $ '
# Use the function given in the tagger variable
tag = getattr(tag_fr, tagger)
try:
tagged = tag(string)
# Use the Stanford tagger if MElt is not installed.
except OSError:
tagged = pos_tag_stanford(string)
tagged = re.sub(ur'\$_.*? ', '$ ', tagged)
words = tagged.split('$')
trimmed = []
for w in words:
w = w.strip()
if w != '':
trimmed.append(w)
return trimmed
