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* Create new API pages and update existing ones * Create query classifier page * Remove Objects suffix
54 lines
1.3 KiB
Markdown
54 lines
1.3 KiB
Markdown
<a name="entity"></a>
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# Module entity
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<a name="entity.EntityExtractor"></a>
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## EntityExtractor
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```python
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class EntityExtractor(BaseComponent)
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```
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This node is used to extract entities out of documents.
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The most common use case for this would be as a named entity extractor.
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The default model used is dslim/bert-base-NER.
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This node can be placed in a querying pipeline to perform entity extraction on retrieved documents only,
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or it can be placed in an indexing pipeline so that all documents in the document store have extracted entities.
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The entities extracted by this Node will populate Document.entities
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<a name="entity.EntityExtractor.run"></a>
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#### run
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```python
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| run(documents: Optional[Union[List[Document], List[dict]]] = None) -> Tuple[Dict, str]
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```
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This is the method called when this node is used in a pipeline
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<a name="entity.EntityExtractor.extract"></a>
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#### extract
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```python
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| extract(text)
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```
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This function can be called to perform entity extraction when using the node in isolation.
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<a name="entity.simplify_ner_for_qa"></a>
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#### simplify\_ner\_for\_qa
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```python
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simplify_ner_for_qa(output)
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```
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Returns a simplified version of the output dictionary
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with the following structure:
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[
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{
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answer: { ... }
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entities: [ { ... }, {} ]
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}
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]
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The entities included are only the ones that overlap with
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the answer itself.
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