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Title:Named entity recognition and linking in PoeTree corpora
Authors:ID Plecháč, Petr (Author)
ID Šeļa, Artjoms (Author)
ID Cinková, Silvie (Author)
ID De Sisto, Mirella (Author)
ID Nugues, Lara (Author)
ID Kočnik, Neža (Author)
ID Kolár, Robert (Author)
ID Haider, Thomas (Author)
Files:.pdf RAZ_Plecháč_Petr_2025.pdf (508,20 KB)
MD5: 6BE729514C66DD67EBA6022F12997958
 
URL https://ojs.utlib.ee/index.php/smp/article/view/26645/20196
 
Language:English
Work type:Scientific work
Typology:1.01 - Original Scientific Article
Organization:FF - Faculty of Arts
Abstract:Named entity recognition (NER) and named entity linking (NEL) remain underexplored in poetic texts. This study provides the first large-scale evaluation of contemporary NER and NEL systems on poetry across seven European languages – Czech, German, English, French, Italian, Russian, and Slovenian – using corpora from the PoeTree project. We benchmark three NER systems (flair, NameTag 2, spaCy) and three GPT models (GPT-3.5, GPT-4, GPT-4 Turbo) against manually annotated gold standards. While results fall short of in-domain benchmarks, they significantly outperform earlier findings. Manual correction further raises final annotation quality to estimated F1 scores between 0.77 and 0.93 across languages. We additionally evaluate two NEL systems – spaCy fishing and mGenre – showing that mGenre consistently outperforms spaCy fishing, achieving in-KB F1-scores of 0.70–0.81. By analysing geographic distances between predicted and gold-standard links, we demonstrate that a substantial portion of “incorrect” predictions are near-miss ambiguities rather than substantive errors. The resulting manually verified geolocation annotations have been integrated into PoeTree and made available through an interactive map interface.
Keywords:poetry, named entities, computational poetics, natural language processing
Publication status:Published
Publication version:Version of Record
Publication date:31.12.2025
Place of publishing:Tartu
Publisher:University of Tartu Press
Year of publishing:2025
Number of pages:str. 7-18
Numbering:Letn. 12, št. 2
PID:20.500.12556/DKUM-98082 New window
UDC:82
ISSN on article:2346-691X
COBISS.SI-ID:277968387 New window
DOI:10.12697/smp.2025.12.2.01 New window
Publication date in DKUM:19.05.2026
Views:118
Downloads:1
Metadata:XML DC-XML DC-RDF
Categories:Misc.
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Record is a part of a journal

Title:Studia Metrica et Poetica
Publisher:University of Tartu Press
ISSN:2346-691X
COBISS.SI-ID:18838275 New window

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:31.12.2025

Secondary language

Language:Slovenian
Keywords:poezija, imenske entitete, računalniška poetika, obdelava naravnega jezika, procesiranje naravnega jezika


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