obama

<p>Parsed text from all eight State of the Union addresses given by
Barack Obama.</p>

data

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, a Python back
end with 'spaCy' <https://spacy.io> or the Java back end 'CoreNLP'
<http://stanfordnlp.github.io/CoreNLP/>. 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

obama: Annotation of Barack Obama's State of the Union Addresses

Description

Arguments

References