Linking Discourse level information and induction of bilingual discourse connective lexicons

Tracking #: 3011-4225

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 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.
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Tags: 
Reviewed

Decision/Status: 
Accept

Solicited Reviews:
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Review #1
Anonymous submitted on 10/Feb/2022
Suggestion:
Accept
Review Comment:

This meta-review addresses the minor modifications implemented in this manuscript, which received an assessment of *accept, accept, and minor revision* in the previous peer-review round.

The minor revision suggested by Reviewer #1 in the previous round concerned linguistic amendments and clarifications. These were related to a description of Connective-Lex, to the need to link TED-MDB data, and to the clarification of specific examples. In this version, these aspects have been successfully addressed and improved.

Following additional amendments suggested to the authors by the guest editorial team, the authors have also included missing clarifications regarding their use of the term “linked data” in this context: the text highlights now that the resource does not yet adhere to LLOD principles and the authors propose next steps in that direction. This new version of the manuscript also shows an explicit clear connection to the state of the art in the representation of discourse information as LLOD.

Note the typo detected in the previous round by Reviewer #1 on p.4, now on l. 20-22, still to be corrected: “This design criterion lead to” > leads to/led to