@inproceedings{lathiff-etal-2021-clac,
title = "{CL}a{C}-np at {S}em{E}val-2021 Task 8: Dependency {DGCNN}",
author = "Lathiff, Nihatha and
Khloponin, Pavel PK and
Bergler, Sabine",
editor = "Palmer, Alexis and
Schneider, Nathan and
Schluter, Natalie and
Emerson, Guy and
Herbelot, Aurelie and
Zhu, Xiaodan",
booktitle = "Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.semeval-1.48",
doi = "10.18653/v1/2021.semeval-1.48",
pages = "404--409",
abstract = "MeasEval aims at identifying quantities along with the entities that are measured with additional properties within English scientific documents. The variety of styles used makes measurements, a most crucial aspect of scientific writing, challenging to extract. This paper presents ablation studies making the case for several preprocessing steps such as specialized tokenization rules. For linguistic structure, we encode dependency trees in a Deep Graph Convolution Network (DGCNN) for multi-task classification.",
}
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<abstract>MeasEval aims at identifying quantities along with the entities that are measured with additional properties within English scientific documents. The variety of styles used makes measurements, a most crucial aspect of scientific writing, challenging to extract. This paper presents ablation studies making the case for several preprocessing steps such as specialized tokenization rules. For linguistic structure, we encode dependency trees in a Deep Graph Convolution Network (DGCNN) for multi-task classification.</abstract>
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%0 Conference Proceedings
%T CLaC-np at SemEval-2021 Task 8: Dependency DGCNN
%A Lathiff, Nihatha
%A Khloponin, Pavel PK
%A Bergler, Sabine
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Schluter, Natalie
%Y Emerson, Guy
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%S Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F lathiff-etal-2021-clac
%X MeasEval aims at identifying quantities along with the entities that are measured with additional properties within English scientific documents. The variety of styles used makes measurements, a most crucial aspect of scientific writing, challenging to extract. This paper presents ablation studies making the case for several preprocessing steps such as specialized tokenization rules. For linguistic structure, we encode dependency trees in a Deep Graph Convolution Network (DGCNN) for multi-task classification.
%R 10.18653/v1/2021.semeval-1.48
%U https://aclanthology.org/2021.semeval-1.48
%U https://doi.org/10.18653/v1/2021.semeval-1.48
%P 404-409
Markdown (Informal)
[CLaC-np at SemEval-2021 Task 8: Dependency DGCNN](https://aclanthology.org/2021.semeval-1.48) (Lathiff et al., SemEval 2021)
ACL
- Nihatha Lathiff, Pavel PK Khloponin, and Sabine Bergler. 2021. CLaC-np at SemEval-2021 Task 8: Dependency DGCNN. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 404–409, Online. Association for Computational Linguistics.