Lemmatization¶

Lemmatization related modeling class

class pororo.tasks.lemmatization.PororoLemmatizationFactory(task: str, lang: str, model: Optional[str])[source]¶

Bases: pororo.tasks.utils.base.PororoFactoryBase

Conduct lemmatization

English (nltk)

dataset: N/A

metric: N/A

Parameters: sent (str) – input sentence to be lemmatized
Returns: lemma list generated by NLTK
Return type: List[str]

Examples

>>> lemma = Pororo(task="lemma", lang="en")
>>> lemma("The striped bats are hanging, on their feet for best.")
['The', 'striped', 'bat', 'be', 'hang', ',', 'on', 'their', 'foot', 'for', 'best',

static get_available_langs()[source]¶

static get_available_models()[source]¶

load(device: str)[source]¶

Load user-selected task-specific model

Parameters: device (str) – device information
Returns: User-selected task-specific model
Return type: object

class pororo.tasks.lemmatization.PororoNLTKLemmatize(nltk, model, config)[source]¶

Bases: pororo.tasks.utils.base.PororoSimpleBase

predict(sent: str, **kwargs)[source]¶

Conduct lemmatization with NLTK module

Parameters: sent (str) – input sentence to be lemmatized
Returns: lemma list generated by NLTK
Return type: List[str]