KnowCoder-X: Boosting Multilingual Information Extraction via Code

• URL: http://arxiv.org/abs/2411.04794v2
• Date: Tue, 08 Apr 2025 16:16:30 GMT
• Title: KnowCoder-X: Boosting Multilingual Information Extraction via Code
• Authors: Yuxin Zuo, Wenxuan Jiang, Wenxuan Liu, Zixuan Li, Long Bai, Hanbin Wang, Yutao Zeng, Xiaolong Jin, Jiafeng Guo, Xueqi Cheng,
• Abstract summary: We propose KnowCoder-X, a code LLM with advanced cross-lingual and multilingual capabilities for universal information extraction.<n>It standardizes the representation of multilingual schemas using Python classes, ensuring a consistent ontology across different languages.<n>KnowCoder-X significantly enhances cross-lingual IE transfer through boosting the IE alignment.
• Score: 62.69772800910482
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Empirical evidence indicates that LLMs exhibit spontaneous cross-lingual alignment. However, although LLMs show promising cross-lingual alignment in IE, a significant imbalance across languages persists, highlighting an underlying deficiency. To address this, we propose KnowCoder-X, a powerful code LLM with advanced cross-lingual and multilingual capabilities for universal information extraction. Firstly, it standardizes the representation of multilingual schemas using Python classes, ensuring a consistent ontology across different languages. Then, IE across languages is formulated as a unified code generation task. Secondly, we enhance the model's cross-lingual transferability through IE cross-lingual alignment instruction tuning on a translated instance prediction task we proposed. During this phase, we also construct a high-quality and diverse bilingual IE parallel dataset with 257k samples, called ParallelNER, synthesized by our proposed robust three-stage pipeline, with manual annotation to ensure quality. Although without training in 29 unseen languages, KnowCoder-X surpasses ChatGPT by $30.17\%$ and SoTA by $20.03\%$, thereby demonstrating superior cross-lingual IE capabilities. Comprehensive evaluations on 64 IE benchmarks in Chinese and English under various settings demonstrate that KnowCoder-X significantly enhances cross-lingual IE transfer through boosting the IE alignment. Our code and dataset are available at: https://github.com/ICT-GoKnow/KnowCoder

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