wordnet | An example web application which is an adaptation | Database library

I need to add the function within the print function to a variable to be calledd to be printed only from the variable name.

My code - for w in processed_H2_tag: print(lemmatizer.lemmatize(w.lower(), pos=wordnet.VERB))

Expected - Print(output)

"Output" is to be defined

I want to use a third-party api: Latin WordNet API, but I meet some problems.

1. The api document shows how to get result by url in browser, but I don't know how to get result by other way.
2. I try to use axios through HTML script element to get the result, like:

I have tried out the following snippet of code for my project:

I have a long list of words :

I have a function which return parts of speech of every word in the form of list of tuples. When I execute it, I only get the the result of first element(first tuple). I want to get the result of every element(tuple) in that list. For eg:

I am working with a computer that can only access to a private network and it cannot send instrunctions from command line. So, whenever I have to install Python packages, I must do it manually (I can't even use Pypi). Luckily, the NLTK allows my to manually download corpora (from here) and to "install" them by putting them in the proper folder (as explained here).

Now, I need to do exactly what is said in this answer:

There are a lot of Q&A about part-of-speech conversion, and they pretty much all point to WordNet derivationally_related_forms() (For example, Convert words between verb/noun/adjective forms)

However, I'm finding that the WordNet data on this has important gaps. For example, I can find no relation at all between 'succeed', 'success', 'successful' which seem like they should be V/N/A variants on the same concept. Likewise none of the lemmatizers I've tried seem to see these as related, although I can get snowball stemmer to turn 'failure' into 'failur' which isn't really much help.

So my questions are:

1. Are there any other (programmatic, ideally python) tools out there that do this POS-conversion, which I should check out? (The WordNet hits are masking every attempt I've made to google alternatives.)
2. Failing that, are there ways to submit additions to WordNet despite the "due to lack of funding" situation they're presently in? (Or, can we set up a crowdfunding campaign?)
3. Failing that, are there straightforward ways to distribute supplementary corpus to users of nltk that augments the WordNet data where needed?

Im creating a Chatbot which uses questions from a CSV file and checks similarity using SKlearn and NLTK, However im getting an error if the same input is entered twice:

This is the main code that takes the user input and outputs an answer to the user:

I am new to NLP. I wish to lemmatise. But understand that for WordNetLemmatizer, it depends on the type of words passed in Noun, Verb, etc.

Hence I tried the below code but it is very slow. Basically all my text are saved in a column called "Text" in df. I use the pre_process(text) function by looping each row (Option 1) but it is v slow.

I tried apply (Option 2) , but it just as slow. Any way to speed up? Thank you!