@inproceedings{tsereteli-etal-2022-overview,
title = "Overview of the {SV}-Ident 2022 Shared Task on Survey Variable Identification in Social Science Publications",
author = "Tsereteli, Tornike and
Kartal, Yavuz Selim and
Ponzetto, Simone Paolo and
Zielinski, Andrea and
Eckert, Kai and
Mayr, Philipp",
editor = "Cohan, Arman and
Feigenblat, Guy and
Freitag, Dayne and
Ghosal, Tirthankar and
Herrmannova, Drahomira and
Knoth, Petr and
Lo, Kyle and
Mayr, Philipp and
Shmueli-Scheuer, Michal and
de Waard, Anita and
Wang, Lucy Lu",
booktitle = "Proceedings of the Third Workshop on Scholarly Document Processing",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.sdp-1.29",
pages = "229--246",
abstract = "In this paper, we provide an overview of the SV-Ident shared task as part of the 3rd Workshop on Scholarly Document Processing (SDP) at COLING 2022. In the shared task, participants were provided with a sentence and a vocabulary of variables, and asked to identify which variables, if any, are mentioned in individual sentences from scholarly documents in full text. Two teams made a total of 9 submissions to the shared task leaderboard. While none of the teams improve on the baseline systems, we still draw insights from their submissions. Furthermore, we provide a detailed evaluation. Data and baselines for our shared task are freely available at \url{https://github.com/vadis-project/sv-ident}.",
}
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%0 Conference Proceedings
%T Overview of the SV-Ident 2022 Shared Task on Survey Variable Identification in Social Science Publications
%A Tsereteli, Tornike
%A Kartal, Yavuz Selim
%A Ponzetto, Simone Paolo
%A Zielinski, Andrea
%A Eckert, Kai
%A Mayr, Philipp
%Y Cohan, Arman
%Y Feigenblat, Guy
%Y Freitag, Dayne
%Y Ghosal, Tirthankar
%Y Herrmannova, Drahomira
%Y Knoth, Petr
%Y Lo, Kyle
%Y Mayr, Philipp
%Y Shmueli-Scheuer, Michal
%Y de Waard, Anita
%Y Wang, Lucy Lu
%S Proceedings of the Third Workshop on Scholarly Document Processing
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F tsereteli-etal-2022-overview
%X In this paper, we provide an overview of the SV-Ident shared task as part of the 3rd Workshop on Scholarly Document Processing (SDP) at COLING 2022. In the shared task, participants were provided with a sentence and a vocabulary of variables, and asked to identify which variables, if any, are mentioned in individual sentences from scholarly documents in full text. Two teams made a total of 9 submissions to the shared task leaderboard. While none of the teams improve on the baseline systems, we still draw insights from their submissions. Furthermore, we provide a detailed evaluation. Data and baselines for our shared task are freely available at https://github.com/vadis-project/sv-ident.
%U https://aclanthology.org/2022.sdp-1.29
%P 229-246
Markdown (Informal)
[Overview of the SV-Ident 2022 Shared Task on Survey Variable Identification in Social Science Publications](https://aclanthology.org/2022.sdp-1.29) (Tsereteli et al., sdp 2022)
ACL