Transformer based named entity recognition for place name extraction from unstructured text

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AUQTD4BJB" target="_blank" >RIV/00216208:11320/23:UQTD4BJB - isvavai.cz</a>

Result on the web

<a href="https://www.tandfonline.com/doi/full/10.1080/13658816.2022.2133125" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/13658816.2022.2133125</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/13658816.2022.2133125" target="_blank" >10.1080/13658816.2022.2133125</a>

Result language

angličtina

Original language name

Transformer based named entity recognition for place name extraction from unstructured text

Original language description

"Place names embedded in online natural language text present a useful source of geographic information. Despite this, many methods for the extraction of place names from text use pre-trained models that were not explicitly designed for this task. Our paper builds five custom-built Named Entity Recognition (NER) models and evaluates them against three popular pre-built models for place name extraction."

Czech name

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Czech description

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Type

J_ost - Miscellaneous article in a specialist periodical

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

"International Journal of Geographical Information Science"

ISSN

1365-8816

e-ISSN

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Volume of the periodical

37

Issue of the periodical within the volume

4

Country of publishing house

US - UNITED STATES

Number of pages

20

Pages from-to

747-766

UT code for WoS article

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EID of the result in the Scopus database

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