mirror of
				https://github.com/explosion/spaCy.git
				synced 2025-11-04 01:48:04 +03:00 
			
		
		
		
	
		
			
				
	
	
		
			81 lines
		
	
	
		
			3.0 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
			
		
		
	
	
			81 lines
		
	
	
		
			3.0 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
//- 💫 DOCS > USAGE > VISUALIZERS > ENTITIES
 | 
						||
 | 
						||
p
 | 
						||
    |  The entity visualizer, #[code ent], highlights named entities and
 | 
						||
    |  their labels in a text.
 | 
						||
 | 
						||
+code("Named Entity example").
 | 
						||
    import spacy
 | 
						||
    from spacy import displacy
 | 
						||
 | 
						||
    text = """But Google is starting from behind. The company made a late push
 | 
						||
    into hardware, and Apple’s Siri, available on iPhones, and Amazon’s Alexa
 | 
						||
    software, which runs on its Echo and Dot devices, have clear leads in
 | 
						||
    consumer adoption."""
 | 
						||
 | 
						||
    nlp = spacy.load('custom_ner_model')
 | 
						||
    doc = nlp(text)
 | 
						||
    displacy.serve(doc, style='ent')
 | 
						||
 | 
						||
+codepen("a73f8b68f9af3157855962b283b364e4", 345)
 | 
						||
 | 
						||
p The entity visualizer lets you customise the following #[code options]:
 | 
						||
 | 
						||
+table(["Name", "Type", "Description", "Default"])
 | 
						||
    +row
 | 
						||
        +cell #[code ents]
 | 
						||
        +cell list
 | 
						||
        +cell
 | 
						||
            |  Entity types to highlight (#[code None] for all types).
 | 
						||
        +cell #[code None]
 | 
						||
 | 
						||
    +row
 | 
						||
        +cell #[code colors]
 | 
						||
        +cell dict
 | 
						||
        +cell
 | 
						||
            |  Color overrides. Entity types in lowercase should be mapped to
 | 
						||
            |  color names or values.
 | 
						||
        +cell #[code {}]
 | 
						||
 | 
						||
p
 | 
						||
    |  If you specify a list of #[code ents], only those entity types will be
 | 
						||
    |  rendered – for example, you can choose to display #[code PERSON] entities.
 | 
						||
    |  Internally, the visualizer knows nothing about available entity types and
 | 
						||
    |  will render whichever spans and labels it receives. This makes it
 | 
						||
    |  especially easy to work with custom entity types. By default, displaCy
 | 
						||
    |  comes with colours for all
 | 
						||
    |  #[+a("/api/annotation#named-entities") entity types supported by spaCy].
 | 
						||
    |  If you're using custom entity types, you can use the #[code colors]
 | 
						||
    |  setting to add your own colours for them.
 | 
						||
 | 
						||
+aside-code("Options example").
 | 
						||
    colors = {'ORG': 'linear-gradient(90deg, #aa9cfc, #fc9ce7)'}
 | 
						||
    options = {'ents': ['ORG'], 'colors': colors}
 | 
						||
    displacy.serve(doc, style='ent', options=options)
 | 
						||
 | 
						||
+codepen("f42ec690762b6f007022a7acd6d0c7d4", 300)
 | 
						||
 | 
						||
p
 | 
						||
    |  The above example uses a little trick: Since the background colour values
 | 
						||
    |  are added as the #[code background] style attribute, you can use any
 | 
						||
    |  #[+a("https://tympanus.net/codrops/css_reference/background/") valid background value]
 | 
						||
    |  or shorthand — including gradients and even images!
 | 
						||
 | 
						||
+h(3, "ent-titles") Adding titles to documents
 | 
						||
 | 
						||
p
 | 
						||
    |  Rendering several large documents on one page can easily become confusing.
 | 
						||
    |  To add a headline to each visualization, you can add a #[code title] to
 | 
						||
    |  its #[code user_data]. User data is never touched or modified by spaCy.
 | 
						||
 | 
						||
+code.
 | 
						||
    doc = nlp(u'This is a sentence about Google.')
 | 
						||
    doc.user_data['title'] = 'This is a title'
 | 
						||
    displacy.serve(doc, style='ent')
 | 
						||
 | 
						||
p
 | 
						||
    |  This feature is espeically handy if you're using displaCy to compare
 | 
						||
    |  performance at different stages of a process, e.g. during training. Here
 | 
						||
    |  you could use the title for a brief description of the text example and
 | 
						||
    |  the number of iterations.
 |