download_core_nlp

type of files to download. The base backage is always required.
Other jars include model files for French, German,
and Spanish. These can be installed in addition to the
base package. By default, the function downloads the base
package and English model files.

type

a string showing where the files are to be downloaded.
If missing, will try to download files into the directory
where the package was original installed.

output_loc

the url to try to download components from. Setting to NULL
uses the default location on the Stanford NLP server, but
you can set this manually by using this option. It also allows
for local files, but note that the path must include the prefix
<code>file://</code>. For details, see <code><a rd-options="" href="/link/download.file?package=cleanNLP&version=1.5.2" data-mini-rdoc="cleanNLP::download.file">download.file</a></code>.

if <code>url</code> is not null, this flag indicates whehter the path
given to url points to the core nlp files (which are zipped) or
to model files (which are unzipped).

url_core

The cleanNLP package does not supply the raw java files
provided by the Stanford NLP Group as they are quite large.
This function downloads the libraries automatically, by default into
the directory where the package was installed. These are not
required for using the spaCy Python implementation.

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

A Tidy Data Model for Natural Language Processing

Taylor B. Arnold

download_core_nlp function

the url to try to download components from. Setting to NULL
uses the default location on the Stanford NLP server, but
you can set this manually by using this option. It also allows
for local files, but note that the path must include the prefix
<code>file://</code>. For details, see <code><a rd-options='' href='download.file'>download.file</a></code>.

Download java files needed for CoreNLP — download_core_nlp

Download java files needed for CoreNLP

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.

download_core_nlp: Download java files needed for CoreNLP

Description

Usage

Arguments

Examples