CLaC-np at SemEval-2021 Task 8: Dependency DGCNN

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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.

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Lathiff, N., Khloponin, P., & Bergler, S. (2021). CLaC-np at SemEval-2021 Task 8: Dependency DGCNN. In SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 404–409). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.semeval-1.48

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