stemexcept

internal

Models for detecting concreteness in natural language. This package is built in support of Yeomans (2021) <doi:10.1016/j.obhdp.2020.10.008>, which reviews linguistic models of concreteness in several domains. Here, we provide an implementation of the best-performing domain-general model (from Brysbaert et al., (2014) <doi:10.3758/s13428-013-0403-5>) as well as two pre-trained models for the feedback and plan-making domains.

Mike Yeomans

doc2concrete

Measuring Concreteness in Natural Language

stemexcept function

<dl><dt>sentence</dt>
<dd>character Vector of sentences to stem.</dd>
<dt>excepts</dt>
<dd>character Vector of words that should not be stemmed.</dd>
<dt>language</dt>
<dd>Language for stemming. Default is "english".</dd></dl>

Arguments

Conditional Stemmer — stemexcept

<dl>

<dt>sentence</dt>
<dd>character Vector of sentences to stem.</dd>


<dt>excepts</dt>
<dd>character Vector of words that should not be stemmed.</dd>


<dt>language</dt>
<dd>Language for stemming. Default is "english".</dd>

</dl>

stemexcept: Conditional Stemmer

Description

Usage

Value

Arguments