rustling.tagging

Part-of-speech tagging.

Package Contents

class rustling.tagging.AveragedPerceptronTagger(*, frequency_threshold: int = 10, ambiguity_threshold: float = 0.95, n_iter: int = 5)

A part-of-speech tagger using an averaged perceptron model.

This is a modified version based on the textblob-aptagger codebase (MIT license), with original implementation by Matthew Honnibal.

predict(words: Sequence[str]) → list[str]

Predict tags for the words.

Parameters:

words – A segmented sentence or phrase, where each word is a string.

Returns:

The list of predicted tags.

fit(tagged_sents: Sequence[Sequence[tuple[str, str]]]) → None

Fit a model.

Parameters:

tagged_sents – A list of segmented and tagged sentences for training. Each sentence is a sequence of (word, tag) tuples.

save(path: str) → None

Save the model to a JSON file.

Parameters:

path – The path where the model will be saved as a JSON file.

load(path: str) → None

Load a model from a JSON file.

Parameters:

path – The path where the model, stored as a JSON file, is located.

Raises:

• FileNotFoundError – If the file at the given path does not exist.

• EnvironmentError – If the file cannot be read as a tagger model.

property weights: dict[str, dict[str, float]]

Get the model’s weights dictionary.

Returns:

A dictionary mapping features to their weight vectors.

property tagdict: dict[str, str]

Get the tag dictionary.

Returns:

A dictionary mapping words to their most likely tags.

property classes: set[str]

Get the set of POS tag classes.

Returns:

A set of all tag classes in the model.