@inproceedings{dellanzo-etal-2020-corpus,
title = "A Corpus for Outbreak Detection of Diseases Prevalent in {L}atin {A}merica",
author = "Dellanzo, Antonella and
Cotik, Viviana and
Ochoa-Luna, Jose",
editor = "Fern{\'a}ndez, Raquel and
Linzen, Tal",
booktitle = "Proceedings of the 24th Conference on Computational Natural Language Learning",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.conll-1.44",
doi = "10.18653/v1/2020.conll-1.44",
pages = "543--551",
abstract = "In this paper we present an annotated corpus which can be used for training and testing algorithms to automatically extract information about diseases outbreaks from news and health reports. We also propose initial approaches to extract information from it. The corpus has been constructed with two main tasks in mind. The first one, to extract entities about outbreaks such as disease, host, location among others. The second one, to retrieve relations among entities, for instance, in such geographic location fifteen cases of a given disease were reported. Overall, our goal is to offer resources and tools to perform an automated analysis so as to support early detection of disease outbreaks and therefore diminish their spreading.",
}
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%0 Conference Proceedings
%T A Corpus for Outbreak Detection of Diseases Prevalent in Latin America
%A Dellanzo, Antonella
%A Cotik, Viviana
%A Ochoa-Luna, Jose
%Y Fernández, Raquel
%Y Linzen, Tal
%S Proceedings of the 24th Conference on Computational Natural Language Learning
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F dellanzo-etal-2020-corpus
%X In this paper we present an annotated corpus which can be used for training and testing algorithms to automatically extract information about diseases outbreaks from news and health reports. We also propose initial approaches to extract information from it. The corpus has been constructed with two main tasks in mind. The first one, to extract entities about outbreaks such as disease, host, location among others. The second one, to retrieve relations among entities, for instance, in such geographic location fifteen cases of a given disease were reported. Overall, our goal is to offer resources and tools to perform an automated analysis so as to support early detection of disease outbreaks and therefore diminish their spreading.
%R 10.18653/v1/2020.conll-1.44
%U https://aclanthology.org/2020.conll-1.44
%U https://doi.org/10.18653/v1/2020.conll-1.44
%P 543-551
Markdown (Informal)
[A Corpus for Outbreak Detection of Diseases Prevalent in Latin America](https://aclanthology.org/2020.conll-1.44) (Dellanzo et al., CoNLL 2020)
ACL