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Automatic Section Recognition in Obituaries
Sabbatino, Valentino; Bostan, Laura Ana Maria; Klinger, Roman (2025): Automatic Section Recognition in Obituaries, in: Bamberg: Otto-Friedrich-Universität, S. 817–825.
Faculty/Chair:
Publisher Information:
Year of publication:
2025
Pages:
Source/Other editions:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, u. a. (Hrsg.), Proceedings of the Twelfth Language Resources and Evaluation Conference, European Language Resources Association, 2020, S. 817–825.
Year of first publication:
2020
Language:
English
Abstract:
Obituaries contain information about people’s values across times and cultures, which makes them a useful resource for exploring cultural history. They are typically structured similarly, with sections corresponding to Personal Information, Biographical Sketch, Characteristics, Family, Gratitude, Tribute, Funeral Information and Other aspects of the person. To make this information available for further studies, we propose a statistical model which recognizes these sections. To achieve that, we collect a corpus of 20058 English obituaries from TheDaily Item, Remembering.CA and The London Free Press. The evaluation of our annotation guidelines with three annotators on 1008 obituaries shows a substantial agreement of Fleiss κ = 0.87. Formulated as an automatic segmentation task, a convolutional neural network outperforms bag-of-words and embedding-based BiLSTMs and BiLSTM-CRFs with a micro F1 = 0.81.
GND Keywords: ; ; ;
Computerlinguistik
Nachruf
Korpus <Linguistik>
Statistisches Modell
Keywords:
Obituaries
DDC Classification:
RVK Classification:
Type:
Conferenceobject
Activation date:
June 2, 2025
Permalink
https://fis.uni-bamberg.de/handle/uniba/108308