Efficiently Filtering List of Keywords using Stemming & Lemmatization

When doing keyword research, we gather keywords from various sources like Keyword Research Tools like ahrefs/semrush, Google Auto Complete, Google Related Searches, Google Search Console Queries, Google Ads Search Term and more.
Then we go through reviewing them one by one before we do keyword mapping. I did share the script for SERP-based Keyword Clustering but to prepare the list of keywords you have to go through filtering and refining this long list.
When the keywords are more than 500 or so, it becomes very difficult to filter out the non-relevant keywords by reviewing them one by one.
The Solution is this Script:
To solve this time-consuming task, I have written a script that takes a list of Keywords. It processes the keywords and creates terms for them.
For example, if the keyword is "audit compliance software" then it will split this keyword into three basic terms "audit", "compliance", and "software".
It goes a step further, it does Stemming and Lemmatization all of these terms and shows you those versions.
So for example, if you choose to use Lemmatized Version then "image" is representative of "imaging", "image" and "images". if you think "image" is not related to your keyword research, then you can discard all the keywords that contain all three above.
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