@inproceedings{hahm-etal-2020-crowdsourcing,
title = "Crowdsourcing in the Development of a Multilingual {F}rame{N}et: A Case Study of {K}orean {F}rame{N}et",
author = "Hahm, Younggyun and
Noh, Youngbin and
Han, Ji Yoon and
Oh, Tae Hwan and
Choe, Hyonsu and
Kim, Hansaem and
Choi, Key-Sun",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.30",
pages = "236--244",
abstract = "Using current methods, the construction of multilingual resources in FrameNet is an expensive and complex task. While crowdsourcing is a viable alternative, it is difficult to include non-native English speakers in such efforts as they often have difficulty with English-based FrameNet tools. In this work, we investigated cross-lingual issues in crowdsourcing approaches for multilingual FrameNets, specifically in the context of the newly constructed Korean FrameNet. To accomplish this, we evaluated the effectiveness of various crowdsourcing settings whereby certain types of information are provided to workers, such as English definitions in FrameNet or translated definitions. We then evaluated whether the crowdsourced results accurately captured the meaning of frames both cross-culturally and cross-linguistically, and found that by allowing the crowd workers to make intuitive choices, they achieved a quality comparable to that of trained FrameNet experts (F1 {\textgreater} 0.75). The outcomes of this work are now publicly available as a new release of Korean FrameNet 1.1.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<abstract>Using current methods, the construction of multilingual resources in FrameNet is an expensive and complex task. While crowdsourcing is a viable alternative, it is difficult to include non-native English speakers in such efforts as they often have difficulty with English-based FrameNet tools. In this work, we investigated cross-lingual issues in crowdsourcing approaches for multilingual FrameNets, specifically in the context of the newly constructed Korean FrameNet. To accomplish this, we evaluated the effectiveness of various crowdsourcing settings whereby certain types of information are provided to workers, such as English definitions in FrameNet or translated definitions. We then evaluated whether the crowdsourced results accurately captured the meaning of frames both cross-culturally and cross-linguistically, and found that by allowing the crowd workers to make intuitive choices, they achieved a quality comparable to that of trained FrameNet experts (F1 \textgreater 0.75). The outcomes of this work are now publicly available as a new release of Korean FrameNet 1.1.</abstract>
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%0 Conference Proceedings
%T Crowdsourcing in the Development of a Multilingual FrameNet: A Case Study of Korean FrameNet
%A Hahm, Younggyun
%A Noh, Youngbin
%A Han, Ji Yoon
%A Oh, Tae Hwan
%A Choe, Hyonsu
%A Kim, Hansaem
%A Choi, Key-Sun
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F hahm-etal-2020-crowdsourcing
%X Using current methods, the construction of multilingual resources in FrameNet is an expensive and complex task. While crowdsourcing is a viable alternative, it is difficult to include non-native English speakers in such efforts as they often have difficulty with English-based FrameNet tools. In this work, we investigated cross-lingual issues in crowdsourcing approaches for multilingual FrameNets, specifically in the context of the newly constructed Korean FrameNet. To accomplish this, we evaluated the effectiveness of various crowdsourcing settings whereby certain types of information are provided to workers, such as English definitions in FrameNet or translated definitions. We then evaluated whether the crowdsourced results accurately captured the meaning of frames both cross-culturally and cross-linguistically, and found that by allowing the crowd workers to make intuitive choices, they achieved a quality comparable to that of trained FrameNet experts (F1 \textgreater 0.75). The outcomes of this work are now publicly available as a new release of Korean FrameNet 1.1.
%U https://aclanthology.org/2020.lrec-1.30
%P 236-244
Markdown (Informal)
[Crowdsourcing in the Development of a Multilingual FrameNet: A Case Study of Korean FrameNet](https://aclanthology.org/2020.lrec-1.30) (Hahm et al., LREC 2020)
ACL