flair.data.Span#

class flair.data.Span(tokens)View on GitHub #

Represents a contiguous sequence of Tokens within a Sentence.

Used for entities, phrases, etc. Implements caching via __new__ within Sentence.

tokens#

The list of tokens constituting the span.

__init__(tokens)View on GitHub #

Initializes the Span (called only once per unique span via __new__).

Parameters:: tokens (list[Token]) – The list of tokens forming the span.

Methods

`__init__`(tokens)	Initializes the Span (called only once per unique span via __new__).
`add_label`(typename, value[, score])	Adds a label, propagating it to the parent Sentence's layer.
`add_metadata`(key, value)	Adds a key-value pair to the data point's metadata.
`clear_embeddings`([embedding_names])	Removes stored embeddings to free memory.
`get_each_embedding`([embedding_names])	Retrieves a list of individual embedding tensors.
`get_embedding`([names])	Retrieves embeddings, concatenating if multiple names are given or if names is None.
`get_label`([label_type, zero_tag_value])	Retrieves the primary label for a given type, or a default 'O' label.
`get_labels`([typename])	Retrieves all labels for a specific annotation layer.
`get_metadata`(key)	Retrieves metadata associated with the given key.
`has_label`(typename)	Checks if the data point has at least one label for the given annotation type.
`has_metadata`(key)	Checks if the data point has metadata for the given key.
`remove_labels`(typename)	Removes labels of a type, also removing them from the parent Sentence layer.
`set_embedding`(name, vector)	Stores an embedding tensor under a given name.
`set_label`(typename, value[, score])	Sets a label (overwriting), propagating the change to the parent Sentence.
`to`(device[, pin_memory])	Moves all stored embedding tensors to the specified device.
`to_dict`([tag_type])

Attributes

`embedding`	Returns embeddings stored directly on the Span object (if any).
`end_position`	Character offset where the span ends (end of the last token, exclusive).
`labels`	Returns a list of all labels from all annotation layers.
`score`	Shortcut property for the score of the first label added.
`start_position`	Character offset where the span begins (start of the first token).
`tag`	Shortcut property for the value of the first label added.
`text`	The combined text of tokens in the span, respecting whitespace offsets.
`unlabeled_identifier`	<end_idx>]: "<text_preview>"'.

property start_position: int#: Character offset where the span begins (start of the first token).

property end_position: int#: Character offset where the span ends (end of the last token, exclusive).

property text: str#: The combined text of tokens in the span, respecting whitespace offsets.

property unlabeled_identifier: str#

<end_idx>]: “<text_preview>”’.

property embedding: Tensor#: Returns embeddings stored directly on the Span object (if any).