Active Learning for Multilingual Semantic Parser

• URL: http://arxiv.org/abs/2301.12920v4
• Date: Wed, 11 Oct 2023 04:08:26 GMT
• Title: Active Learning for Multilingual Semantic Parser
• Authors: Zhuang Li, Gholamreza Haffari
• Abstract summary: We propose the first active learning procedure for multilingual semantic parsing (AL-MSP) AL-MSP selects only a subset from the existing datasets to be translated. Our experiments show that AL-MSP significantly reduces translation costs with ideal selection methods.
• Score: 65.2180122032335
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Current multilingual semantic parsing (MSP) datasets are almost all collected by translating the utterances in the existing datasets from the resource-rich language to the target language. However, manual translation is costly. To reduce the translation effort, this paper proposes the first active learning procedure for MSP (AL-MSP). AL-MSP selects only a subset from the existing datasets to be translated. We also propose a novel selection method that prioritizes the examples diversifying the logical form structures with more lexical choices, and a novel hyperparameter tuning method that needs no extra annotation cost. Our experiments show that AL-MSP significantly reduces translation costs with ideal selection methods. Our selection method with proper hyperparameters yields better parsing performance than the other baselines on two multilingual datasets.

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