Institutional Repository of Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Set Generation Networks for End-to-End Knowledge Base Population | |
Sui DB(隋典伯)1,2; Chenhao Wang1,2; Yubo Chen1,2; Kang Liu1,2; Jun Zhao1,2; Wei Bi3 | |
2021-11 | |
会议名称 | Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing |
会议日期 | 2021-11 |
会议地点 | Online and Punta Cana, Dominican Republic |
摘要 | The task of knowledge base population (KBP) aims to discover facts about entities from texts and expand a knowledge base with these facts. Previous studies shape end-to-end KBP as a machine translation task, which is required to convert unordered fact into a sequence according to a pre-specified order. However, the facts stated in a sentence are unordered in essence. In this paper, we formulate end-to-end KBP as a direct set generation problem, avoiding considering the order of multiple facts. To solve the set generation problem, we propose networks featured by transformers with non-autoregressive parallel decoding. Unlike previous approaches that use an autoregressive decoder to generate facts one by one, the proposed networks can directly output the final set of facts in one shot. Furthermore, to train the networks, we also design a set-based loss that forces unique predictions via bipartite matching. Compared with cross-entropy loss that highly penalizes small shifts in fact order, the proposed bipartite matching loss is invariant to any permutation of predictions. Benefiting from getting rid of the burden of predicting the order of multiple facts, our proposed networks achieve state-of-the-art (SoTA) performance on two benchmark datasets. |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48934 |
专题 | 模式识别国家重点实验室_自然语言处理 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, CAS 2.School of Artificial Intelligence, University of Chinese Academy of Sciences 3.Tencent AI Lab |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Sui DB,Chenhao Wang,Yubo Chen,et al. Set Generation Networks for End-to-End Knowledge Base Population[C],2021. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
2021.emnlp-main.760.(552KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论