spaCy - Span Class Properties

In this chapter, let us learn the Span properties in spaCy.

Properties

Following are the properties with regards to Span Class in spaCy.

Span.ents

This Span property is used for the named entities in the span. If the entity recogniser has been appped, this property will return a tuple of named entity span objects.

Example 1

An example of Span.ents property is as follows −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("This is Tutorialspoint.com.")
span = doc[0:5]
ents = pst(span.ents)
ents[0].label

Output

You will receive the following output −

383

Example 2

An another example of Span.ents property is as follows −

ents[0].label_

Output

You will receive the following output −

‘ORG’

Example 3

Given below is another example of Span.ents property −

ents[0].text

Output

You will receive the following output −

 Tutorialspoint.com 

Span.as_doc

As the name suggests, this Span property will create a new Doc object corresponding to the Span. It will have a copy of data too.

Example

An example of Span.as_doc property is given below −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("I pke India.")
span = doc[2:4]
doc2 = span.as_doc()
doc2.text

Output

You will receive the following output −

India

Span.root

This Span property will provide the token with the shortest path to the root of the sentence. It will take the first token, if there are multiple tokens which are equally high in the tree.

Example 1

An example of Span.root property is as follows −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("I pke New York in Autumn.")
i, pke, new, york, in_, autumn, dot = range(len(doc))
doc[new].head.text

Output

You will receive the following output −

 York 

Example 2

An another example of Span.root property is as follows −

doc[york].head.text

Output

You will receive the following output −

 pke 

Example 3

Given below is an example of Span.root property −

new_york = doc[new:york+1]
new_york.root.text

Output

You will receive the following output −

 York 

Span.lefts

This Span property is used for the tokens that are to the left of the span, whose heads are within the span.

Example

An example of Span.lefts property is mentioned below −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("This is Tutorialspoint.com.")
lefts = [t.text for t in doc[1:4].lefts]
lefts

Output

You will receive the following output −

[ This ]

Span.rights

This Span property is used for the tokens that are to the right of the span whose heads are within the span.

Example

An example of Span.rights property is given below −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("This is Tutorialspoint.com.")
rights = [t.text for t in doc[1:2].rights]
rights

Output

You will receive the following output −

[ Tutorialspoint.com ,  . ]

Span.n_rights

This Span property is used for the tokens that are to the right of the span whose heads are within the span.

Example

An example of Span.n_rights property is as follows −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("This is Tutorialspoint.com.")
doc[1:2].n_rights

Output

You will receive the following output −

2

Span.n_lefts

This Span property is used for the tokens that are to the left of the span whose heads are within the span.

Example

An example of Span.n_lefts property is as follows −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("This is Tutorialspoint.com.")
doc[1:2].n_lefts

Output

You will receive the following output −

1

Span.subtree

This Span property yields the tokens that are within the span and the tokens which descend from them.

Example

An example of Span.subtree property is as follows −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("This is Tutorialspoint.com.")
subtree = [t.text for t in doc[:1].subtree]
subtree

Output

You will receive the following output −

[ This ]

Span.vector

This Span property represents a real-valued meaning. The defaults value is an average of the token vectors.

Example 1

An example of Span.vector property is as follows −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("The website is Tutorialspoint.com.")
doc[1:].vector.dtype

Output

You will receive the following output −

dtype( float32 )

Example 2

An another example of Span.vector property is as follows −

Output

You will receive the following output −

(96,)

Span.vector_norm

This doc property represents the L2 norm of the document’s vector representation.

Example

An example of Span.vector_norm property is as follows −

import spacy
nlp_model = spacy.load("en_core_web_sm")
doc = nlp_model("The website is Tutorialspoint.com.")
doc[1:].vector_norm
doc[2:].vector_norm
doc[1:].vector_norm != doc[2:].vector_norm

Output

You will receive the following output −

True