COMBO-NLP - A library for Morphosyntactic Tagging and Dependency Parsing.
Project description
COMBO-NLP
A library for Morphosyntactic Tagging and Dependency Parsing based on Universal Dependencies.
Installation
pip install combo-nlp
LAMBO segmenter (optional)
A segmenter is only needed when passing raw text strings to COMBO. If you provide pre-tokenized input (list[str] or list[list[str]]), no segmenter is required.
When you initialize COMBO with a language name (e.g. COMBO("Polish")), it automatically loads a LAMBO segmenter. If LAMBO is not installed, an ImportError is raised. LAMBO is hosted on a custom PyPI index and must be installed separately:
pip install --index-url https://pypi.clarin-pl.eu/ lambo
Usage
Full text input
from combo import COMBO
# Load by HuggingFace model ID:
nlp = COMBO.from_pretrained("clarin-pl/combo-nlp-xlm-roberta-base-polish-pdb-ud2.17")
result = nlp("Ala ma kota.")
# Or load by language name (with Lambo segmenter):
nlp = COMBO("Polish")
result = nlp("Ala ma kota.")
# Or use the Language enum:
from combo import Language
nlp = COMBO(Language.POLISH)
result = nlp("Ala ma kota.")
# Multiple sentences:
result = nlp(["Ala ma kota.", "Pies je."])
# Access results:
for sentence in result:
for token in sentence:
print(token.form, token.upos, token.head, token.deprel, token.lemma)
Pre-tokenized input
from combo import COMBO
nlp = COMBO.from_pretrained("clarin-pl/combo-nlp-xlm-roberta-base-polish-pdb-ud2.17")
# Single sentence:
result = nlp(["Ala", "ma", "kota", "."], tokenized=True)
# Multiple sentences:
result = nlp([["Ala", "ma", "kota", "."], ["Pies", "je", "."]], tokenized=True)
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