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extr

Named Entity Recognition (NER) and Relation Extraction (RE) library using Regular Expressions

  • 0.0.44
  • PyPI
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Maintainers
1

Extr

Named Entity Recognition (NER) and Relation Extraction (RE) library using Regular Expressions


Install

pip install extr

Example

text = 'Ted is a Pitcher.'

1. Entity Extraction

Find Named Entities from text.

from extr import RegEx, RegExLabel
from extr.entities import EntityExtractor

entity_extractor = EntityExtractor([
    RegExLabel('PERSON', [
        RegEx([r'ted'], re.IGNORECASE)
    ]),
    RegExLabel('POSITION', [
        RegEx([r'pitcher'], re.IGNORECASE)
    ]),
])

entities = entity_extractor.get_entities(text)

## entities == [
##      <Entity label="POSITION" text="Pitcher" span=(9, 16)>,
##      <Entity label="PERSON" text="Ted" span=(0, 3)>
## ]

or add a knowledge base

from extr import RegEx, RegExLabel
from extr.entities import create_entity_extractor

entity_extractor = create_entity_extractor(
    [
        RegExLabel('POSITION', [
            RegEx([r'pitcher'], re.IGNORECASE)
        ]),
    ],
    kb={
        'PERSON': ['Ted']
    }
)

entities = entity_extractor.get_entities(text)

## entities == [
##      <Entity label="POSITION" text="Pitcher" span=(9, 16)>,
##      <Entity label="PERSON" text="Ted" span=(0, 3)>
## ]

2. Visualize Entities in HTML

Annotate text to display in HTML.

from extr.entities.viewers import HtmlViewer

viewer = HtmlViewer()
viewer.append(text, entities)

html = viewer.create_view(custom_styles="""
    .lb-PERSON {
        background-color: orange;
    }

    .lb-POSITION {
        background-color: yellow;
    }
""")

3. Relation Extraction

Annotate and Extract Relationships between Entities

from extr.entities import EntityAnnotator
from extr.relations import RelationExtractor, \
                           RegExRelationLabelBuilder

## define relationship between PERSON and POSITION
relationship = RegExRelationLabelBuilder('is_a') \
    .add_e1_to_e2(
        'PERSON', ## e1
        [
            ## define how the relationship exists in nature
            r'\s+is\s+a\s+',
        ],
        'POSITION' ## e2
    ) \
    .build()

relations_to_extract = [relationship]

## `entities` see 'Entity Extraction' above
annotated_text = EntityAnnotator().annotate(text, entities)
relations = RelationExtractor(relations_to_extract).extract(annotated_text, entities)

## relations == [
##      <Relation e1="Ted" r="is_a" e2="Pitcher">
## ]

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