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NLP | Part of speech — default tags

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What is part-of-speech (POS) tagging?
This is the process of converting sentences to forms — a list of words, a list of tuples (where each tuple is of the form (word, tag) ). The tag in the case of a word is a part of speech tag and indicates whether the word is a noun, adjective, verb, etc.

Default Marking is the basic step for part-of-speech marking. This is done using the DefaultTagger class. The DefaultTagger class takes a tag as its only argument.  NN — it is a tag for a singular noun.  DefaultTagger is most useful when it works with the most common part of speech tag. This is why the noun tag is recommended.

Code # 1: How does it work?

# Loading libraries

from nltk.tag import DefaultTagger

 
# Tag definition

tagging = DefaultTagger ( ’ NN’ )

 
# Tagging

tagging.tag ([ ’Hello’ , ’ Geeks’ ] )

Output:

 [(’Hello’,’ NN’), (’Geeks’,’ NN’)] 

Each tagger has a tag () method that accepts a list of tokens (usually a list of words generated by a word tokenizer) where each token is a separate word.  tag () returns a list of tagged tokens — a tuple of.

How does DefaultTagger work?
This is a subclass of SequentialBackoffTagger and implements a choose_tag () method that has three arguments.

  • list of tokens
  • Index of the current token to select a tag.
  • list of previous tags

Code # 2: Marking Offers

# Loading libraries

from nltk.tag import DefaultTagger

 
# Tag definition

tagging = DefaultTagger ( ’NN’ )

 

 

tagging.tag_sents ([[ ’welcome’ , ’to’ , ’ .’ ], [ ’Geeks’ , ’ for’ , ’Geeks’ ]])

Output:

 [[(’welcome’, ’NN’), (’ to’, ’NN’), (’ .’, ’NN’)], [(’ Geeks’, ’NN’), (’ for’, ’NN’), (’ Geeks ’,’ NN’)]] 

Note. Each tag in the tagged offer list (in the code above) is NN, because we used the DefaultTagger class .

Code # 3: Illustrating how to mark up.

from nltk.tag import untag

untag ([( ’Geeks’ , ’NN’ ), ( ’ for’ , ’ NN’ ), ( ’Geeks’ , ’NN’ )])

Output:

 [’Geeks’ , ’for’,’ Geeks’] 

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