def tryer(self, i, kw, tag):
regex = self.regex
w = self.dictionnary
test_wd = clean(basify(kw)).lower()
reg = [r for r in regex if r[0] == tag][0]
to_remove_from_d = reg[1]
pseudo_end = reg[2]
if to_remove_from_d > 0:
test_wd = test_wd[:-to_remove_from_d + i] + pseudo_end
sh = w
keep = np.where(np.asarray([distance(test_wd, s) for s in sh]) == 0)
if len(keep[0]) > 0:
final = np.asarray(sh)[keep]
else:
keep = np.where(
np.asarray([distance(test_wd, s) for s in sh]) == 1)
if len(keep[0]) > 0:
final = np.asarray(sh)[keep]
else:
keep = np.where(
np.asarray([distance(test_wd, s) for s in sh]) == 2)
if len(keep[0]) > 0:
final = np.asarray(sh)[keep]
else:
final = np.asarray(w)[self.last_chance(kw)]
return final
def dict_lemmatizer(self, st):
lemmatizer = self.lemma
st = clean(basify(st)).lower()
try:
out = lemmatizer[lemmatizer[0]==st].values[0][1]
except IndexError:
out = 'unk'
return out
def levdist_lemmatizer(self, kw, i=0):
w = self.dictionnary
test_wd = clean(basify(kw)).lower()
keep = np.where(np.asarray([distance(test_wd,s) for s in w])==i)
if len(keep[0]) > 0:
final = keep[0][0]
out = w[final]
else:
out = 'unk'
return out
def dummy_lemma(self, kw, tag):
regex = self.regex
w = self.dictionnary
test_wd = clean(basify(kw)).lower()
reg = [r for r in regex if r[0] == tag][0]
to_remove_from_d = reg[1]
pseudo_end = reg[2]
if to_remove_from_d is not None and to_remove_from_d > 0:
test_wd = test_wd[:-to_remove_from_d] + pseudo_end
return test_wd
def get_tags(path):
r = Replacer()
entire_treebank = path
with open(entire_treebank, 'r') as f:
xml_string = f.read()
root = etree.fromstring(xml_string)
body = root.findall('body')[0]
sentences = body.findall('sentence')
sentences_list = []
for sentence in sentences:
words_list = sentence.findall('word')
sentence_list = []
for x in words_list:
word = x.attrib
form = word['form'].upper()
form = r.beta_code(form)
try:
if form[-1] == 's':
form = form[:-1] + '?'
except IndexError:
pass
form = form.lower()
form = clean(basify(form))
form_list = [
char for char in form
if char not in [' ', "'", '?', '’', '[', ']']
]
form = ''.join(form_list)
try:
postag1 = word['postag']
postag1 = postag1
postag2 = word['lemma']
postag2 = clean(basify(postag2))
except:
postag = 'x--------'
if len(form) == 0: continue
word_tag = '/'.join([form, postag1, postag2])
sentence_list.append(word_tag)
sentence_str = ' '.join(sentence_list)
sentences_list.append(sentence_str)
treebank_training_set = '\n\n'.join(sentences_list)
return treebank_training_set
def tag(self, st):
to_pos = clean(basify(st)).lower().split()
wd_list = self.tnt_tot._wd.keys()
to_pos_unk = [item for item in to_pos if item not in list(wd_list)]
print("nb of unk wd "+str(len(to_pos_unk)))
print(to_pos_unk)
if len(to_pos_unk)>0:
tnt_new = tnt.TnT()
tnt_new.train([self.top_k_wd(wd, 2) for wd in to_pos_unk])
self.tnt_tot._wd = tnt_new._wd.__add__(self.tnt_tot._wd)
return self.tnt_tot.tag(to_pos)
def last_chance(self, kw):
w = self.dictionnary
no_find = True
i = 0
while no_find:
test_wd = clean(basify(kw)).lower()
keep = np.where(np.asarray([distance(test_wd, s) for s in w]) == i)
if len(keep[0]) > 0:
no_find = False
final = keep[0][0]
i = i + 1
if i > 3:
final = 'unk'
return final
def pos_lemmatizer(self, kw, tag, rk = 0):
regex = self.regex
w = self.dictionnary
test_wd = clean(basify(kw)).lower()
try:
reg=[r for r in regex if r[0]==tag][0]
except IndexError:
reg=[0,0,None]
to_remove_from_d = reg[1]
pseudo_end = reg[2]
if to_remove_from_d is not None and to_remove_from_d > 0:
test_wd = test_wd[:-to_remove_from_d] + pseudo_end
sh = w
keep = np.where(np.asarray([distance(test_wd,s) for s in sh])==rk)
if len(keep[0])>0:
final = np.asarray(sh)[keep]
max_lcs = np.argmax([lcs(kw, i) for i in list(final)])
final = list(final)[max_lcs]
else:
final = 'unk'
return final
def st_to_lemma(self, st):
ta = self.CltkTnt
lemma = []
tagged = ta.tag(st)
to_pos = clean(basify(st)).lower().split()
len_st = len(to_pos)
for i in range(len_st):
try:
le = self.lemmatize(to_pos[i])
except IndexError:
try:
le = self.tryer(0, *tagged[i])
if type(le) == np.str_:
le = le
elif len(le) > 0:
le = le[0]
else:
le = 'unk'
except IndexError:
le = 'unk'
lemma.append(le)
print(le)
out = lemma
return out
def greek_to_token(self, wrd):
input=" ".join(list(clean(basify(wrd))))
sequences = self.tok.texts_to_sequences([input])
sequences_matrix = sequence.pad_sequences(sequences, maxlen=16)
out = to_categorical(sequences_matrix[0], num_classes=self.alpha).reshape(1, 16, self.alpha)
return out
def get_root(self):
wd = self.word_string.split("/")[2]
wd = wd.lower()
wd = clean(basify(wd))
return wd
def sentence_to_lemma(self, st):
to = clean(basify(st))
all_w = [list(word) for word in to.split()]
to_tok = [" ".join(a) for a in all_w]
return [self.attention_lemmatizer(target) for target in to_tok]
