FinnTransFrame : translating frames in the FinnFrameNet project

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http://hdl.handle.net/10138/266770

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Lindén , K , Haltia , H , Laine , A , Luukkonen , J , Piitulainen , J & Väisänen , N 2019 , ' FinnTransFrame : translating frames in the FinnFrameNet project ' , Language Resources and Evaluation , vol. 53 , no. 1 , pp. 141-171 . https://doi.org/10.1007/s10579-018-9434-y

Title: FinnTransFrame : translating frames in the FinnFrameNet project
Author: Lindén, Krister; Haltia, Heidi; Laine, Antti; Luukkonen, Juha; Piitulainen, Jussi; Väisänen, Niina
Contributor organization: Centre of Excellence in Ancient Near Eastern Empires (ANEE)
Department of Digital Humanities
Language Technology
Doctoral Programme in Language Studies
University Management
Department of Modern Languages 2010-2017
Department of World Cultures 2010-2017
Faculty of Arts
Department of Finnish, Finno-Ugrian and Scandinavian Studies
Date: 2019
Language: eng
Number of pages: 31
Belongs to series: Language Resources and Evaluation
ISSN: 1574-0218
DOI: https://doi.org/10.1007/s10579-018-9434-y
URI: http://hdl.handle.net/10138/266770
Abstract: The article details the formational process of the FinnTransFrame corpus, a part of the FinnFrameNet project. In addition to a large annotated frame semantic corpus of natural language examples, the project created a separate corpus of examples translated from English to Finnish. The research question when creating the FinnTransFrame corpus was to see to what extent the various frames of the original Berkeley FrameNet transfer into Finnish in translated examples, i.e. what are the main problems and how can they be categorized? A variety of Berkeley FrameNet examples were chosen from different frames and then translated by professionals. The FinnFrameNet annotation team checked all the examples and their translations to see if the frames remained intact in translation. Problematic examples were tagged according to the type of the encountered problem, with the main focus on the type of fine-grained mismatches of meaning that caused frame changes even when the translation was the best possible one. The frame-loss amounted to 4.2% of the 88,209 relevant example sentences. Filtering out sentences with other types of problems, we found that 88.1% of all the frame instances still translated into Finnish with their frame intact. In addition, the article analyzes the error types in the problematic frames.
Subject: 6121 Languages
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


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