Linking discourselevel information and induction of bilingual discourse connective lexicons

Tracking #: 2898-4112

This paper is currently under review
Authors: 
Sibel Özer
Murathan Kurfali
Deniz Zeyrek
Amalia Mendes
Giedrė Valūnaitė Oleškevičienė

Responsible editor: 
Guest Editors Advancements in Linguistics Linked Data 2021

Submission type: 
Full Paper
Abstract: 
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 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 high accuracy, as verified against the semi-automatically linked relations of three diverse languages. The resulting corpus has a great potential to reveal the divergences the languages exhibit in local discourse relations, with respect to the source text, as well as leading to new resources, as exemplified by the induction of bilingual discourse connective lexicons.
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Under Review