airbnb_chunks

The <code><a rd-options="" href="/link/airbnb?package=crfsuite&version=0.3.1" data-mini-rdoc="crfsuite::airbnb">airbnb</a></code> dataset was manually annotated with the shiny app inside this R package.
The annotation shows chunks of data which have been flagged with the following categories: PERSON, LOCATION, DISTANCE.
The dataset is an object of class <code>chunkrange</code> and of type data.frame which contains the following fields:<ul>
<li>doc_id: a unique identifier of the review, which is also available in <code><a rd-options="" href="/link/airbnb?package=crfsuite&version=0.3.1" data-mini-rdoc="crfsuite::airbnb">airbnb</a></code></li>
<li>listing_id: the airbnb address identifier</li>
<li>text: text with the feedback of a customer on his visit in the AirBnB appartment</li>
<li>chunk_id: a chunk identifier</li>
<li>chunk_entity: a chunk entity label</li>
<li>chunk: the text of the chunk which is a substring of <code>text</code></li>
<li>start: the starting position in <code>text</code> where the <code>chunk</code> is found</li>
<li>end: the end position in <code>text</code> where the <code>chunk</code> is found</li>
</ul>

Wraps the 'CRFsuite' library <https://github.com/chokkan/crfsuite> allowing users
to fit a Conditional Random Field model and to apply it on existing data.
The focus of the implementation is in the area of Natural Language Processing where this R package allows you to easily build and apply models
for named entity recognition, text chunking, part of speech tagging, intent recognition or classification of any category you have in mind. Next to training, a small web application
is included in the package to allow you to easily construct training data.

Jan Wijffels

crfsuite

Conditional Random Fields for Labelling Sequential Data in
Natural Language Processing

BNOSAC 

Naoaki Okazaki

Bob Jenkins

Jorge Nocedal

Jesse Long

airbnb_chunks function

The <code><a rd-options='' href='airbnb'>airbnb</a></code> dataset was manually annotated with the shiny app inside this R package.
The annotation shows chunks of data which have been flagged with the following categories: PERSON, LOCATION, DISTANCE.
The dataset is an object of class <code>chunkrange</code> and of type data.frame which contains the following fields:<ul>
<li>doc_id: a unique identifier of the review, which is also available in <code><a rd-options='' href='airbnb'>airbnb</a></code></li>
<li>listing_id: the airbnb address identifier</li>
<li>text: text with the feedback of a customer on his visit in the AirBnB appartment</li>
<li>chunk_id: a chunk identifier</li>
<li>chunk_entity: a chunk entity label</li>
<li>chunk: the text of the chunk which is a substring of <code>text</code></li>
<li>start: the starting position in <code>text</code> where the <code>chunk</code> is found</li>
<li>end: the end position in <code>text</code> where the <code>chunk</code> is found</li>
</ul>

Dutch reviews of AirBnB customers on Brussels address locations manually tagged with entities — airbnb_chunks

Dutch reviews of AirBnB customers on Brussels address locations manually tagged with entities

airbnb_chunks: Dutch reviews of AirBnB customers on Brussels address locations manually tagged with entities

Description

Arguments

See Also

Examples