Neural cross-lingual event detection with minimal parallel resources | |
Liu, Jian1,2; Chen, Yubo2; Liu, Kang1,2; Zhao, Jun1,2 | |
2019-11 | |
会议日期 | 2019-11 |
会议地点 | 香港 |
页码 | 738-748 |
英文摘要 | The scarcity in annotated data poses a great challenge for event detection (ED). Cross-lingual ED aims to tackle this challenge by transferring knowledge between different languages to boost performance. However, previous cross-lingual methods for ED demonstrated a heavy dependency on parallel resources, which might limit their applicability. In this paper, we propose a new method for cross-lingual ED, demonstrating a minimal dependency on parallel resources. Specifically, to construct a lexical mapping between different languages, we devise a context-dependent translation method; to treat the word order difference problem, we propose a shared syntactic order event detector for multilingual co-training. The efficiency of our method is studied through extensive experiments on two standard datasets. Empirical results indicate that our method is effective in 1) performing cross-lingual transfer concerning different directions and 2) tackling the extremely annotation-poor scenario. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/39209] ![]() |
专题 | 模式识别国家重点实验室_自然语言处理 |
作者单位 | 1.中国科学院大学 2.中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Liu, Jian,Chen, Yubo,Liu, Kang,et al. Neural cross-lingual event detection with minimal parallel resources[C]. 见:. 香港. 2019-11. |
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