word_frequency

<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>

data

Provides a set of fast tools for converting a textual corpus into a set of normalized
tables. Users may make use of a Python back end with 'spaCy' <https://spacy.io>
or the Java back end 'CoreNLP' <http://stanfordnlp.github.io/CoreNLP/>. A minimal back
end with no external dependencies is also provided. Exposed annotation tasks include
tokenization, part of speech tagging, named entity recognition, entity linking, sentiment
analysis, dependency parsing, coreference resolution, and word embeddings. Summary
statistics regarding token unigram, part of speech tag, and dependency type frequencies
are also included to assist with analyses.

Taylor Arnold

cleanNLP

word_frequency: Most frequent English words

Description

Arguments

References