extr 0.0.44

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

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">
## ]