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remove universe object: spacy-lookup
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@ -967,34 +967,6 @@
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},
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"category": ["pipeline"]
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},
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{
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"id": "spacy-lookup",
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"slogan": "A powerful entity matcher for very large dictionaries, using the FlashText module",
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"description": "spaCy v2.0 extension and pipeline component for adding Named Entities metadata to `Doc` objects. Detects Named Entities using dictionaries. The extension sets the custom `Doc`, `Token` and `Span` attributes `._.is_entity`, `._.entity_type`, `._.has_entities` and `._.entities`. Named Entities are matched using the python module `flashtext`, and looked up in the data provided by different dictionaries.",
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"github": "mpuig/spacy-lookup",
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"pip": "spacy-lookup",
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"code_example": [
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"import spacy",
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"from spacy_lookup import Entity",
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"",
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"nlp = spacy.load('en')",
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"entity = Entity(keywords_list=['python', 'product manager', 'java platform'])",
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"nlp.add_pipe(entity, last=True)",
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"",
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"doc = nlp(\"I am a product manager for a java and python.\")",
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"assert doc._.has_entities == True",
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"assert doc[0]._.is_entity == False",
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"assert doc[3]._.entity_desc == 'product manager'",
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"assert doc[3]._.is_entity == True",
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"",
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"print([(token.text, token._.canonical) for token in doc if token._.is_entity])"
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],
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"author": "Marc Puig",
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"author_links": {
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"github": "mpuig"
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},
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"category": ["pipeline"]
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},
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{
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"id": "spacy-iwnlp",
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"slogan": "German lemmatization with IWNLP",
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