Python NLTK Program for Lemmatization words

Python NLTK Program for Lemmatization words


Lemmatization is the algorithmic process of finding the lemma of a word depending on its meaning.

Lemmatization usually refers to the morphological analysis of words, which aims to remove inflectional endings.

It helps in returning the base or dictionary form of a word, which is known as the lemma.

The NLTK Lemmatization the method is based on WorldNet's built-in morph function.

Text pre-processing includes both stemming as well as lemmatization. Many people find the two terms confusing. Some treat these as same, but there is a difference between these both.

Why is Lemmatization better than Stemming?

The stemming algorithm works by cutting the suffix from the word. In a broader sense cuts either the beginning or end of the word.

On the contrary, Lemmatization is a more powerful operation, and it takes into consideration morphological analysis of the words.

It returns the lemma which is the base form of all its inflectional forms. In-depth linguistic knowledge is required to create dictionaries and look for the proper form of the word.

Stemming is a general operation while lemmatization is an intelligent operation where the proper form will be looked in the dictionary. Hence, lemmatization helps in forming better machine learning features.

Program for Lemmatization words Using NLTK:



Lemmatization is much better than stemming.