overlaps

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

overlaps function

<dl><dt>high</dt>
<dd>matrix Token counts that will all be kept.</dd>
<dt>low</dt>
<dd>matrix Token counts that will evaluated (and pruned) for overlapping.</dd>
<dt>cutoff</dt>
<dd>numeric Threshold (as cosine distance) for including overlapping tokens. Default is 1 (i.e. all tokens included).</dd></dl>

Arguments

Overlap cleaner — overlaps

<dl>

<dt>high</dt>
<dd>matrix Token counts that will all be kept.</dd>


<dt>low</dt>
<dd>matrix Token counts that will evaluated (and pruned) for overlapping.</dd>


<dt>cutoff</dt>
<dd>numeric Threshold (as cosine distance) for including overlapping tokens. Default is 1 (i.e. all tokens included).</dd>

</dl>

overlaps: Overlap cleaner

Description

Usage

Value

Arguments