TY  - CONF
A1  - Chiarcos, Christian
A1  - Schenk, Niko
A1  - Fäth, Christian
A2  - Kernerman, Ilan
A2  - Krek, Simon
A2  - McCrae, John P.
A2  - Gracia, Jorge
A2  - Ahmadi, Sina
A2  - Kabashi, Besim
T1  - Translation inference by concept propagation
T2  - Proceedings of the 2020 Globalex Workshop on Linked Lexicography, 11–16 May 2020, Marseille, France
N2  - 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 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.
Y1  - 2023
UR  - https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/104026
UR  - https://nbn-resolving.org/urn:nbn:de:bvb:384-opus4-1040264
UR  - https://aclanthology.org/2020.globalex-1.16
SN  - 979-10-95546-46-7
SP  - 98
EP  - 105
PB  - European Language Resources Association
CY  - Paris
ER  -