Blog #17

Blog #13

 30 Oct 2017

During my MSc a few years ago whilst specialising in machine learning, sentiment analysis and Bayesian theorem, I encountered a technique that I could use to improve the computers understanding of human language,  called POS Tagging.

What is POS Tagging?

POS tagging is the process of assigning a ‘tag/category’ (in the form of an abbreviated code) to each word (token) in a given sentence.

In the English language for example, common POS categories are:

  • nouns
  • verbs
  • adjectives
  • adverbs
  • pronouns
  • prepositions
  • conjunctions
  • interjections

Other categories can be derived from different forms of the above, for example a verb can be in its base form or in past tense.

Penn Treebank POS Tags

For the purposes of this blog post I have focussed on the Penn Treebank POS Tag Set.  You can see the entire list of these POS Tags in the below table:
 

Tag

Description

Tag

Description

CC

Coordinating conjunction

PRP$

Possessive pronoun

CD

Cardinal number

RB

Adverb

DT

Determiner

RBR

Adverb, comparative

EX

Existential there

RBS

Adverb, superlative

FW

Foreign word

RP

Particle

IN

Preposition or subordinating conjunction

SYM

Symbol

JJ

Adjective

TO

to

JJR

Adjective, comparative

UH

Interjection

JJS

Adjective, superlative

VB

Verb, base form

LS

List item marker

VBD

Verb, past tense

MD

Modal

VBG

Verb, gerund or present participle

NN

Noun, singular or mass

VBN

Verb, past participle

NNS

Noun, plural

VBP

Verb, non-3rd person singular present

NNP

Proper noun, singular

VBZ

Verb, 3rd person singular present

NNPS

Proper noun, plural

WDT

Wh-determiner

PDT

Predeterminer

WP

Wh-pronoun

POS

Possessive ending

WP$

Possessive wh-pronoun

PRP

Personal pronoun

WRB

Wh-adverb


So how do I use this?
 

If you'd like to find out how to use POS tagging, click the image below to Download our Sentiment Analysis Whitepaper.

Or View Our Diary And Book In A Call

Also included in the Whitepaper:

  • Bayesian Theorem & It's Connection To Sentiment Analysis
  • The Difficulties Of Sentiment Analysis & The Solutions
  • How To Train Your Classifier When Performing Sentiment Analysis

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