def align_entity_types(self, sample: InputSample) -> None:
"""
Translates the sample's tags to the ones requested by the model
:param sample: Input sample
:return: None
"""
if self.entity_mapping:
sample.translate_input_sample_tags(dictionary=self.entity_mapping)
def predict(self, sample: InputSample) -> List[str]:
if self.translate_to_spacy_entities:
sample.translate_input_sample_tags()
doc = self.model(sample.full_text)
tags = self.get_tags_from_doc(doc)
if len(doc) != len(sample.tokens):
print("mismatch between input tokens and new tokens")
return tags
def predict(self, sample: InputSample) -> List[str]:
if self.translate_to_spacy_entities:
sample.translate_input_sample_tags()
sentence = Sentence(text=sample.full_text, use_tokenizer=self.spacy_tokenizer)
self.model.predict(sentence)
tags = self.get_tags_from_sentence(sentence)
if len(tags) != len(sample.tokens):
print("mismatch between previous tokens and new tokens")
return tags