Translation inference by concept propagation
- This paper describes our contribution to the Third Shared Task on Translation Inference across Dictionaries (TIAD-2020). We describe an approach on translation inference based on symbolic methods, the propagation of concepts over a graph of interconnected dictionaries: Given a mapping from source language words to lexical concepts (e.g., synsets) as a seed, we use bilingual dictionaries to extrapolate a mapping of pivot and target language words to these lexical concepts. Translation inference is then performed by looking up the lexical concept(s) of a source language word and returning the target language word(s) for which these lexical concepts have the respective highest score. We present two instantiations of this system: One using WordNet synsets as concepts, and one using lexical entries (translations) as concepts. With a threshold of 0, the latter configuration is the second among participant systems in terms of F1 score. We also describe additional evaluation experiments onThis paper describes our contribution to the Third Shared Task on Translation Inference across Dictionaries (TIAD-2020). We describe an approach on translation inference based on symbolic methods, the propagation of concepts over a graph of interconnected dictionaries: Given a mapping from source language words to lexical concepts (e.g., synsets) as a seed, we use bilingual dictionaries to extrapolate a mapping of pivot and target language words to these lexical concepts. Translation inference is then performed by looking up the lexical concept(s) of a source language word and returning the target language word(s) for which these lexical concepts have the respective highest score. We present two instantiations of this system: One using WordNet synsets as concepts, and one using lexical entries (translations) as concepts. With a threshold of 0, the latter configuration is the second among participant systems in terms of F1 score. We also describe additional evaluation experiments on Apertium data, a comparison with an earlier approach based on embedding projection, and an approach for constrained projection that outperforms the TIAD-2020 vanilla system by a large margin.…
Author: | Christian ChiarcosORCiDGND, Niko Schenk, Christian Fäth |
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URN: | urn:nbn:de:bvb:384-opus4-1040264 |
Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/104026 |
URL: | https://aclanthology.org/2020.globalex-1.16 |
ISBN: | 979-10-95546-46-7OPAC |
Parent Title (English): | Proceedings of the 2020 Globalex Workshop on Linked Lexicography, 11–16 May 2020, Marseille, France |
Publisher: | European Language Resources Association |
Place of publication: | Paris |
Editor: | Ilan Kernerman, Simon Krek, John P. McCrae, Jorge Gracia, Sina Ahmadi, Besim Kabashi |
Type: | Conference Proceeding |
Language: | English |
Year of first Publication: | 2020 |
Publishing Institution: | Universität Augsburg |
Release Date: | 2023/05/15 |
First Page: | 98 |
Last Page: | 105 |
Institutes: | Philologisch-Historische Fakultät |
Philologisch-Historische Fakultät / Angewandte Computerlinguistik | |
Philologisch-Historische Fakultät / Angewandte Computerlinguistik / Lehrstuhl für Angewandte Computerlinguistik (ACoLi) | |
Dewey Decimal Classification: | 4 Sprache / 40 Sprache / 400 Sprache |
Licence (German): | CC-BY-NC 4.0: Creative Commons: Namensnennung - Nicht kommerziell (mit Print on Demand) |