def segment_text(self, text):
"""Segment the provided text into sentences."""
self.tokenizer.setText(text)
is_another = True
sentences = []
while is_another:
u_sentence = Sentence()
is_another = self.tokenizer.nextSentence(u_sentence)
if is_another:
sentences.append(u_sentence.getText())
return sentences
def _runApp(self, dto, opNotDone):
text = dto.getText()
tokenizer = self._model.newTokenizer(self._model.DEFAULT)
tokenizer.setText(text)
error = ProcessingError()
sentence = Sentence()
sid = 0
while tokenizer.nextSentence(sentence, error):
self._model.tag(sentence, self._model.DEFAULT)
self._model.parse(sentence, self._model.DEFAULT)
# Teprolin tokenized sentence
ttsent = []
# Teprolin string sentence
tssent = sentence.getText()
for w in sentence.words:
if w.id == 0:
continue
tt = TeproTok()
tt.setId(w.id)
tt.setWordForm(w.form)
tt.setCTAG(w.upostag)
tt.setMSD(w.xpostag)
tt.setLemma(w.lemma)
tt.setHead(w.head)
tt.setDepRel(w.deprel)
ttsent.append(tt)
# end for w
if not dto.isOpPerformed(TeproAlgo.getSentenceSplittingOperName()):
dto.addSentenceString(tssent)
dto.addSentenceTokens(ttsent)
else:
# Check and update annotations that only TTL
# can produce or that are requested specifically from it.
alignment = dto.alignSentences(ttsent, sid)
for op in opNotDone:
dto.copyTokenAnnotation(ttsent, sid, alignment, op)
sentence = Sentence()
sid += 1
# end all split sentences.
return dto
def tokenize_tag_parse_tree(self,
root,
resegment=False,
tag=True,
parse=True):
"""Tokenize, tag (+lemmatize, fill FEATS) and parse the text stored in `root.text`.
If resegment=True, the returned list of Udapi trees may contain multiple trees.
"""
if root.children:
raise ValueError(
'Tree already contained nodes before tokenization')
# Tokenize and segment the text (segmentation cannot be turned off in older UDPipe versions).
self.tokenizer.setText(root.text)
is_another = True
u_sentences = []
while is_another:
u_sentence = Sentence()
is_another = self.tokenizer.nextSentence(u_sentence)
if is_another:
u_sentences.append(u_sentence)
# If resegmentation was not required, we need to join the segments.
if not resegment and len(u_sentences) > 1:
first_sent = u_sentences[0]
n_words = first_sent.words.size() - 1
for other_sent in u_sentences[1:]:
other_words = other_sent.words.size() - 1
for i in range(1, other_words + 1):
u_w = other_sent.words[i]
n_words += 1
u_w.id = n_words
first_sent.words.append(u_w)
u_sentences = [first_sent]
# tagging and parsing
if tag:
for u_sentence in u_sentences:
self.tool.tag(u_sentence, Model.DEFAULT)
if parse:
self.tool.parse(u_sentence, Model.DEFAULT)
elif parse:
raise ValueError(
'Combination parse=True tag=False is not allowed.')
# converting UDPipe nodes to Udapi nodes
new_root = root
trees = []
for u_sentence in u_sentences:
if not new_root:
new_root = Root()
new_root.text = u_sentence.getText() if resegment else root.text
heads, nodes = [], [new_root]
u_words = u_sentence.words
for i in range(1, u_words.size()):
u_w = u_words[i]
node = new_root.create_child(
form=u_w.form,
lemma=u_w.lemma,
upos=u_w.upostag,
xpos=u_w.xpostag,
feats=u_w.feats,
deprel=u_w.deprel,
misc=u_w.misc,
)
if parse:
heads.append(u_w.head)
nodes.append(node)
if parse:
for node in nodes[1:]:
head = heads.pop(0)
node.parent = nodes[head]
trees.append(new_root)
new_root = None
return trees
