How to Install and Uninstall perl-Lingua-EN-Tagger.x86_64 Package on Fedora 38
Last updated: November 14,2024
1. Install "perl-Lingua-EN-Tagger.x86_64" package
This guide let you learn how to install perl-Lingua-EN-Tagger.x86_64 on Fedora 38
$
sudo dnf update
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$
sudo dnf install
perl-Lingua-EN-Tagger.x86_64
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2. Uninstall "perl-Lingua-EN-Tagger.x86_64" package
Please follow the step by step instructions below to uninstall perl-Lingua-EN-Tagger.x86_64 on Fedora 38:
$
sudo dnf remove
perl-Lingua-EN-Tagger.x86_64
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$
sudo dnf autoremove
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3. Information about the perl-Lingua-EN-Tagger.x86_64 package on Fedora 38
Last metadata expiration check: 1:53:58 ago on Sat Mar 16 16:59:57 2024.
Available Packages
Name : perl-Lingua-EN-Tagger
Version : 0.31
Release : 12.fc38
Architecture : x86_64
Size : 485 k
Source : perl-Lingua-EN-Tagger-0.31-12.fc38.src.rpm
Repository : fedora
Summary : Part-of-speech tagger for English natural language processing
URL : https://metacpan.org/release/Lingua-EN-Tagger
License : GPLv3
Description : The module is a probability based, corpus-trained tagger that assigns POS
: tags to English text based on a lookup dictionary and a set of probability
: values. The tagger assigns appropriate tags based on conditional
: probabilities - it examines the preceding tag to determine the appropriate
: tag for the current word. Unknown words are classified according to word
: morphology or can be set to be treated as nouns or other parts of speech.
Available Packages
Name : perl-Lingua-EN-Tagger
Version : 0.31
Release : 12.fc38
Architecture : x86_64
Size : 485 k
Source : perl-Lingua-EN-Tagger-0.31-12.fc38.src.rpm
Repository : fedora
Summary : Part-of-speech tagger for English natural language processing
URL : https://metacpan.org/release/Lingua-EN-Tagger
License : GPLv3
Description : The module is a probability based, corpus-trained tagger that assigns POS
: tags to English text based on a lookup dictionary and a set of probability
: values. The tagger assigns appropriate tags based on conditional
: probabilities - it examines the preceding tag to determine the appropriate
: tag for the current word. Unknown words are classified according to word
: morphology or can be set to be treated as nouns or other parts of speech.