@inproceedings{jenkins-etal-2023-massively,
title = "Massively Multi-Lingual Event Understanding: Extraction, Visualization, and Search",
author = "Jenkins, Chris and
Agarwal, Shantanu and
Barry, Joel and
Fincke, Steven and
Boschee, Elizabeth",
editor = "Bollegala, Danushka and
Huang, Ruihong and
Ritter, Alan",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-demo.23",
doi = "10.18653/v1/2023.acl-demo.23",
pages = "247--256",
abstract = "In this paper, we present ISI-Clear, a state-of-the-art, cross-lingual, zero-shot event extraction system and accompanying user interface for event visualization {\&} search. Using only English training data, ISI-Clear makes global events available on-demand, processing user-supplied text in 100 languages ranging from Afrikaans to Yiddish. We provide multiple event-centric views of extracted events, including both a graphical representation and a document-level summary. We also integrate existing cross-lingual search algorithms with event extraction capabilities to provide cross-lingual event-centric search, allowing English-speaking users to search over events automatically extracted from a corpus of non-English documents, using either English natural language queries (e.g. {``}cholera outbreaks in Iran{''}) or structured queries (e.g. find all events of type Disease-Outbreak with agent {``}cholera{''} and location {``}Iran{''}).",
}
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<abstract>In this paper, we present ISI-Clear, a state-of-the-art, cross-lingual, zero-shot event extraction system and accompanying user interface for event visualization & search. Using only English training data, ISI-Clear makes global events available on-demand, processing user-supplied text in 100 languages ranging from Afrikaans to Yiddish. We provide multiple event-centric views of extracted events, including both a graphical representation and a document-level summary. We also integrate existing cross-lingual search algorithms with event extraction capabilities to provide cross-lingual event-centric search, allowing English-speaking users to search over events automatically extracted from a corpus of non-English documents, using either English natural language queries (e.g. “cholera outbreaks in Iran”) or structured queries (e.g. find all events of type Disease-Outbreak with agent “cholera” and location “Iran”).</abstract>
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%0 Conference Proceedings
%T Massively Multi-Lingual Event Understanding: Extraction, Visualization, and Search
%A Jenkins, Chris
%A Agarwal, Shantanu
%A Barry, Joel
%A Fincke, Steven
%A Boschee, Elizabeth
%Y Bollegala, Danushka
%Y Huang, Ruihong
%Y Ritter, Alan
%S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F jenkins-etal-2023-massively
%X In this paper, we present ISI-Clear, a state-of-the-art, cross-lingual, zero-shot event extraction system and accompanying user interface for event visualization & search. Using only English training data, ISI-Clear makes global events available on-demand, processing user-supplied text in 100 languages ranging from Afrikaans to Yiddish. We provide multiple event-centric views of extracted events, including both a graphical representation and a document-level summary. We also integrate existing cross-lingual search algorithms with event extraction capabilities to provide cross-lingual event-centric search, allowing English-speaking users to search over events automatically extracted from a corpus of non-English documents, using either English natural language queries (e.g. “cholera outbreaks in Iran”) or structured queries (e.g. find all events of type Disease-Outbreak with agent “cholera” and location “Iran”).
%R 10.18653/v1/2023.acl-demo.23
%U https://aclanthology.org/2023.acl-demo.23
%U https://doi.org/10.18653/v1/2023.acl-demo.23
%P 247-256
Markdown (Informal)
[Massively Multi-Lingual Event Understanding: Extraction, Visualization, and Search](https://aclanthology.org/2023.acl-demo.23) (Jenkins et al., ACL 2023)
ACL