How to Install and Uninstall wordnet-sense-index Package on Ubuntu 23.10 (Mantic Minotaur)

Last updated: May 20,2024

1. Install "wordnet-sense-index" package

This guide covers the steps necessary to install wordnet-sense-index on Ubuntu 23.10 (Mantic Minotaur)


    
        
            $
        

        
            
                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                wordnet-sense-index
            
                    
    
    Copied

2. Uninstall "wordnet-sense-index" package

Please follow the steps below to uninstall wordnet-sense-index on Ubuntu 23.10 (Mantic Minotaur):


    
        
            $
        

        
            
                sudo apt remove
            
                        
                wordnet-sense-index
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the wordnet-sense-index package on Ubuntu 23.10 (Mantic Minotaur)

Package: wordnet-sense-index
Architecture: all
Version: 1:3.0-37
Priority: optional
Section: universe/text
Source: wordnet
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 8045
Recommends: wordnet
Filename: pool/universe/w/wordnet/wordnet-sense-index_3.0-37_all.deb
Size: 1697134
MD5sum: a3f2432fe74f514040e82aabcc4c08f2
SHA1: 523229c95235c8426e5fbcf3c81c7dff91c5465b
SHA256: f5ea424251c931d0ae9c3c692874686068fb0364ed70571d9b64fc8e710b1b47
SHA512: 20ead2e20c50feacad067f2adfebca04c4a576ff84a13812038487d16a4ee8a5a397efb5917654f604ffd6fb97327d8e15bb93e8de68e7d292b482f6454934c2
Homepage: http://wordnet.princeton.edu/
Description: electronic lexical database of English language (index)
Description-md5: 2ffca7e7c45e20f656d0323b731662df