GLiNER Mentions Extractor

GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.

The GLiNER mentions extractor will use the mentions specified in the zshot.PipelineConfig, it just uses the names of the mentions, it doesn't use the descriptions of the mentions.

• Paper
• Original Source Code

Bases: MentionsExtractor

GLiNER Mentions Extractor

load_models()

Load GLINER model

predict(docs, batch_size=None)

Perform the entity prediction

Parameters:

Name	Type	Description	Default
docs	Iterator[Doc]	A list of spacy Document	required
batch_size	Optional[Union[int, None]]	The batch size	None

Returns:

Type	Description
List[List[Span]]	List Spans for each Document in docs