Enhanced Universal Dependency Parsing with Second-Order Inference and Mixture of Training Data

June 02, 2020 ยท Declared Dead ยท ๐Ÿ› International Workshop/Conference on Parsing Technologies

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Authors Xinyu Wang, Yong Jiang, Kewei Tu arXiv ID 2006.01414 Category cs.CL: Computation & Language Cross-listed cs.LG Citations 11 Venue International Workshop/Conference on Parsing Technologies Last Checked 5 months ago
Abstract
This paper presents the system used in our submission to the \textit{IWPT 2020 Shared Task}. Our system is a graph-based parser with second-order inference. For the low-resource Tamil corpus, we specially mixed the training data of Tamil with other languages and significantly improved the performance of Tamil. Due to our misunderstanding of the submission requirements, we submitted graphs that are not connected, which makes our system only rank \textbf{6th} over 10 teams. However, after we fixed this problem, our system is 0.6 ELAS higher than the team that ranked \textbf{1st} in the official results.
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