@inproceedings{piad-morffis-etal-2019-general,
title = "A General-Purpose Annotation Model for Knowledge Discovery: Case Study in {S}panish Clinical Text",
author = "Piad-Morffis, Alejandro and
Guit{\'e}rrez, Yoan and
Estevez-Velarde, Suilan and
Mu{\~n}oz, Rafael",
editor = "Rumshisky, Anna and
Roberts, Kirk and
Bethard, Steven and
Naumann, Tristan",
booktitle = "Proceedings of the 2nd Clinical Natural Language Processing Workshop",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-1910",
doi = "10.18653/v1/W19-1910",
pages = "79--88",
abstract = "Knowledge discovery from text in natural language is a task usually aided by the manual construction of annotated corpora. Specifically in the clinical domain, several annotation models are used depending on the characteristics of the task to solve (e.g., named entity recognition, relation extraction, etc.). However, few general-purpose annotation models exist, that can support a broad range of knowledge extraction tasks. This paper presents an annotation model designed to capture a large portion of the semantics of natural language text. The structure of the annotation model is presented, with examples of annotated sentences and a brief description of each semantic role and relation defined. This research focuses on an application to clinical texts in the Spanish language. Nevertheless, the presented annotation model is extensible to other domains and languages. An example of annotated sentences, guidelines, and suitable configuration files for an annotation tool are also provided for the research community.",
}
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<abstract>Knowledge discovery from text in natural language is a task usually aided by the manual construction of annotated corpora. Specifically in the clinical domain, several annotation models are used depending on the characteristics of the task to solve (e.g., named entity recognition, relation extraction, etc.). However, few general-purpose annotation models exist, that can support a broad range of knowledge extraction tasks. This paper presents an annotation model designed to capture a large portion of the semantics of natural language text. The structure of the annotation model is presented, with examples of annotated sentences and a brief description of each semantic role and relation defined. This research focuses on an application to clinical texts in the Spanish language. Nevertheless, the presented annotation model is extensible to other domains and languages. An example of annotated sentences, guidelines, and suitable configuration files for an annotation tool are also provided for the research community.</abstract>
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%0 Conference Proceedings
%T A General-Purpose Annotation Model for Knowledge Discovery: Case Study in Spanish Clinical Text
%A Piad-Morffis, Alejandro
%A Guitérrez, Yoan
%A Estevez-Velarde, Suilan
%A Muñoz, Rafael
%Y Rumshisky, Anna
%Y Roberts, Kirk
%Y Bethard, Steven
%Y Naumann, Tristan
%S Proceedings of the 2nd Clinical Natural Language Processing Workshop
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F piad-morffis-etal-2019-general
%X Knowledge discovery from text in natural language is a task usually aided by the manual construction of annotated corpora. Specifically in the clinical domain, several annotation models are used depending on the characteristics of the task to solve (e.g., named entity recognition, relation extraction, etc.). However, few general-purpose annotation models exist, that can support a broad range of knowledge extraction tasks. This paper presents an annotation model designed to capture a large portion of the semantics of natural language text. The structure of the annotation model is presented, with examples of annotated sentences and a brief description of each semantic role and relation defined. This research focuses on an application to clinical texts in the Spanish language. Nevertheless, the presented annotation model is extensible to other domains and languages. An example of annotated sentences, guidelines, and suitable configuration files for an annotation tool are also provided for the research community.
%R 10.18653/v1/W19-1910
%U https://aclanthology.org/W19-1910
%U https://doi.org/10.18653/v1/W19-1910
%P 79-88
Markdown (Informal)
[A General-Purpose Annotation Model for Knowledge Discovery: Case Study in Spanish Clinical Text](https://aclanthology.org/W19-1910) (Piad-Morffis et al., ClinicalNLP 2019)
ACL