Translating entity names, especially when a literal translation is not correct, poses a significant challenge. Although Machine Translation (MT) systems have achieved impressive results, they still struggle to translate cultural nuances and language-specific context. In this work, we show that the integration of multilingual knowledge graphs into MT systems can address this problem and bring two significant benefits: i) improving the translation of utterances that contain entities by leveraging their human-curated aliases from a multilingual knowledge graph, and, ii) increasing the interpretability of the translation process by providing the user with information from the knowledge graph.
Enhancing Machine Translation Experiences with Multilingual Knowledge Graphs / Conia, Simone; Lee, Daniel; Li, Min; Minhas, Umar Farooq; Li, Yunyao. - 38:21(2024), pp. 23781-23783. (Intervento presentato al convegno National Conference of the American Association for Artificial Intelligence tenutosi a Vancouver; Canada) [10.1609/aaai.v38i21.30563].
Enhancing Machine Translation Experiences with Multilingual Knowledge Graphs
Conia, Simone
Primo
;
2024
Abstract
Translating entity names, especially when a literal translation is not correct, poses a significant challenge. Although Machine Translation (MT) systems have achieved impressive results, they still struggle to translate cultural nuances and language-specific context. In this work, we show that the integration of multilingual knowledge graphs into MT systems can address this problem and bring two significant benefits: i) improving the translation of utterances that contain entities by leveraging their human-curated aliases from a multilingual knowledge graph, and, ii) increasing the interpretability of the translation process by providing the user with information from the knowledge graph.File | Dimensione | Formato | |
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