no code implementations • LREC 2020 • Christos Rodosthenous, Verena Lyding, Federico Sangati, Alex K{\"o}nig, er, Umair ul Hassan, Lionel Nicolas, Jolita Horbacauskiene, Anisia Katinskaia, Lavinia Aparaschivei
In this work, we report on a crowdsourcing experiment conducted using the V-TREL vocabulary trainer which is accessed via a Telegram chatbot interface to gather knowledge on word relations suitable for expanding ConceptNet.
no code implementations • LREC 2020 • Lionel Nicolas, Verena Lyding, Claudia Borg, Corina Forascu, Kar{\"e}n Fort, Katerina Zdravkova, Iztok Kosem, Jaka {\v{C}}ibej, {\v{S}}pela Arhar Holdt, Alice Millour, Alex K{\"o}nig, er, Christos Rodosthenous, Federico Sangati, Umair ul Hassan, Anisia Katinskaia, Anabela Barreiro, Lavinia Aparaschivei, Yaakov HaCohen-Kerner
We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved.
no code implementations • RANLP 2019 • Verena Lyding, Christos Rodosthenous, Federico Sangati, Umair ul Hassan, Lionel Nicolas, Alex K{\"o}nig, er, Jolita Horbacauskiene, Anisia Katinskaia
In this paper, we present our work on developing a vocabulary trainer that uses exercises generated from language resources such as ConceptNet and crowdsources the responses of the learners to enrich the language resource.
no code implementations • 28 Jul 2018 • Christos Rodosthenous, Loizos Michael
We present Web-STAR, an online platform for story understanding built on top of the STAR reasoning engine for STory comprehension through ARgumentation.
no code implementations • 20 Jun 2017 • Christos Rodosthenous, Loizos Michael
In this work, we present Web-STAR, an online platform for story understanding built on top of the STAR (STory comprehension through ARgumentation) reasoning engine.