Knowledge Commons of Institute of Automation,CAS
Neural cross-lingual event detection with minimal parallel resources | |
Liu, Jian1,2![]() ![]() ![]() ![]() | |
2019-11 | |
会议名称 | Empirical Methods in Natural Language Processing |
页码 | 738-748 |
会议日期 | 2019-11 |
会议地点 | 香港 |
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. |
收录类别 | EI |
七大方向——子方向分类 | 自然语言处理 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39209 |
专题 | 多模态人工智能系统全国重点实验室_自然语言处理 |
作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 |
第一作者单位 | 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],2019:738-748. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
D19-1068.pdf(843KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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