Provides a set of fast tools for converting a textual corpus into
a set of normalized tables. Users may make use of the 'udpipe' back end with
no external dependencies, or two Python back ends with 'spaCy'
<https://spacy.io> or 'CoreNLP' <https://stanfordnlp.github.io/CoreNLP/>.
Exposed annotation tasks include tokenization, part of speech tagging, named
entity recognition, and dependency parsing.

A Tidy Data Model for Natural Language Processing

package-ubuntu-20.04-r-4.0.5#cran#cleanNLP-3.0.3

<p>A dataset of the 150k most frequently used English words, extracted by
Peter Norvig from the Google Web Trillion Word Corpus. Frequencies are
multiplied by 100.
</p>

<p><a href="https://norvig.com/ngrams/">https://norvig.com/ngrams/</a>
</p>

package-ubuntu-20.04-r-4.0.5#cran#cleanNLP-3.0.3#docs#word_frequency

word_frequency

Description

References

cleanNLP

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