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The process of lemmatization in natural language processing involves working with words according to their root lexical components. It is used in natural language processing and natural language understanding in computer programming and artificial intelligence.
The specific discipline of lemmatization is a subcategory of a process called stemming. In natural language processing, stemming allows the computer to group together words according to their various inflections that are tagged with a particular stem. For instance: “walk,” “walked” and “walking.”
Lemmatization is a bit more complex in that the computer can group together words that do not have the same stem, but still have the same inflected meaning. Grouping the word “good” with words like “better” and “best” is an example of lemmatization. Lemmatization is also a harbinger of increased artificial intelligence sophistication – as natural language processing advances in accommodating lemmatization, it is more able to parse inputs and provide intelligent outputs. This will be an important aspect of NLP as technology gets closer to passing the Turing test with computers that hear, understand, think and speak like humans.