Linking discourse-level information and the induction of bilingual discourse connective lexicons

Özer, Sibel
Kurfall, Murathan
Zeyrek Bozşahin, Deniz
Mendes, Amália
Oleškevičiene, Giedre Valunaite
The single biggest obstacle in performing comprehensive cross-lingual discourse analysis is the scarcity of multilingual resources. The existing resources are overwhelmingly monolingual, compelling researchers to infer the discourse-level information in the target languages through error-prone automatic means. The current paper aims to provide a more direct insight into the cross-lingual variations in discourse structures by linking the annotated relations of the TED-Multilingual Discourse Bank, which consists of independently annotated six TED talks in seven different languages. It is shown that the linguistic labels over the relations annotated in the texts of these languages can be automatically linked with English with high accuracy, as verified against the relations of three diverse languages semi-automatically linked with relations over English texts. The resulting corpus has a great potential to reveal the divergences in local discourse relations, as well as leading to new resources, as exemplified by the induction of bilingual discourse connective lexicons.
Semantic Web


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Citation Formats
S. Özer, M. Kurfall, D. Zeyrek Bozşahin, A. Mendes, and G. V. Oleškevičiene, “Linking discourse-level information and the induction of bilingual discourse connective lexicons,” Semantic Web, vol. 13, no. 6, pp. 1081–1102, 2022, Accessed: 00, 2023. [Online]. Available: