@inproceedings{gupta-etal-2017-identifying,
title = "Identifying Comparative Structures in Biomedical Text",
author = "Gupta, Samir and
Mahmood, A.S.M. Ashique and
Ross, Karen and
Wu, Cathy and
Vijay-Shanker, K.",
editor = "Cohen, Kevin Bretonnel and
Demner-Fushman, Dina and
Ananiadou, Sophia and
Tsujii, Junichi",
booktitle = "{B}io{NLP} 2017",
month = aug,
year = "2017",
address = "Vancouver, Canada,",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-2326",
doi = "10.18653/v1/W17-2326",
pages = "206--215",
abstract = "Comparison sentences are very commonly used by authors in biomedical literature to report results of experiments. In such comparisons, authors typically make observations under two different scenarios. In this paper, we present a system to automatically identify such comparative sentences and their components i.e. the compared entities, the scale of the comparison and the aspect on which the entities are being compared. Our methodology is based on dependencies obtained by applying a parser to extract a wide range of comparison structures. We evaluated our system for its effectiveness in identifying comparisons and their components. The system achieved a F-score of 0.87 for comparison sentence identification and 0.77-0.81 for identifying its components.",
}
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<abstract>Comparison sentences are very commonly used by authors in biomedical literature to report results of experiments. In such comparisons, authors typically make observations under two different scenarios. In this paper, we present a system to automatically identify such comparative sentences and their components i.e. the compared entities, the scale of the comparison and the aspect on which the entities are being compared. Our methodology is based on dependencies obtained by applying a parser to extract a wide range of comparison structures. We evaluated our system for its effectiveness in identifying comparisons and their components. The system achieved a F-score of 0.87 for comparison sentence identification and 0.77-0.81 for identifying its components.</abstract>
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%0 Conference Proceedings
%T Identifying Comparative Structures in Biomedical Text
%A Gupta, Samir
%A Mahmood, A.S.M. Ashique
%A Ross, Karen
%A Wu, Cathy
%A Vijay-Shanker, K.
%Y Cohen, Kevin Bretonnel
%Y Demner-Fushman, Dina
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S BioNLP 2017
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada,
%F gupta-etal-2017-identifying
%X Comparison sentences are very commonly used by authors in biomedical literature to report results of experiments. In such comparisons, authors typically make observations under two different scenarios. In this paper, we present a system to automatically identify such comparative sentences and their components i.e. the compared entities, the scale of the comparison and the aspect on which the entities are being compared. Our methodology is based on dependencies obtained by applying a parser to extract a wide range of comparison structures. We evaluated our system for its effectiveness in identifying comparisons and their components. The system achieved a F-score of 0.87 for comparison sentence identification and 0.77-0.81 for identifying its components.
%R 10.18653/v1/W17-2326
%U https://aclanthology.org/W17-2326
%U https://doi.org/10.18653/v1/W17-2326
%P 206-215
Markdown (Informal)
[Identifying Comparative Structures in Biomedical Text](https://aclanthology.org/W17-2326) (Gupta et al., BioNLP 2017)
ACL