<jupyter_start><jupyter_text><jupyter_code>import spacy
!pip install --upgrade spacy
!pip install -U spacy-lookups-data
!python -m spacy download pt_core_news_lg
text = "Os Giants começaram com a posse de bola, e mostraram logo que iriam alongar ao máximo suas posses de bola."

nlp = spacy.load("pt_core_news_lg")
doc = nlp(text)

etiquetas = [(token.orth_,token.tag_) for token in doc]
print(etiquetas)<jupyter_output><empty_output><jupyter_text>spaCY - Entidades Nomeadas<jupyter_code><jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10038610038610038, 'fraction_numerical': 0.0, 'mean_word_length': 6.746268656716418, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '528531', 'license': 'MIT', 'n_tokens_mistral': 208, 'n_tokens_neox': 201, 'n_words': 49, 'path': 'Aula_3_spaCY.ipynb', 'repo_name': 'Muramatsu2602/nlp-intro', 'size': '518'}