People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00130934" target="_blank" >RIV/00216224:14330/23:00130934 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2023.findings-acl.887" target="_blank" >https://aclanthology.org/2023.findings-acl.887</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts
Original language description
<p>Although pre-trained named entity recognition (NER) models are highly accurate on modern corpora, they underperform on historical texts due to differences in language OCR errors. In this work, we develop a new NER corpus of 3.6M sentences from late medieval charters written mainly in Czech, Latin, and German.</p> <p>We show that we can start with a list of known historical figures and locations and an unannotated corpus of historical texts, and use information retrieval techniques to automatically bootstrap a NER-annotated corpus. Using our corpus, we train a NER model that achieves entity-level Precision of 72.81-93.98% with 58.14-81.77% Recall on a manually-annotated test dataset. Furthermore, we show that using a weighted loss function helps to combat class imbalance in token classification tasks. To make it easy for others to reproduce and build upon our work, we publicly release our corpus, models, and experimental code.</p>
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Findings of the Association for Computational Linguistics: ACL 2023
ISBN
9781959429623
ISSN
0736-587X
e-ISSN
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Number of pages
10
Pages from-to
14104-14113
Publisher name
Association for Computational Linguistics
Place of publication
Toronto, Canada
Event location
Toronto, Canada
Event date
Jul 9, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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