分类:Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy

Bowen Yu and Zhenyu Zhang and Xiaobo Shu and Tingwen Liu Yubin Wang and Bin Wang and Sujian L. ECAI2020

Abstract

Joint extraction of entities and relations aims to detect entity pairs along with their relations using a single model. Prior work typically solves this task in the extract-then-classify or unified labeling manner. However, these methods either suffer from the re- dundant entity pairs, or ignore the important inner structure in the process of extracting entities and relations. To address these limita- tions, in this paper, we first decompose the joint extraction task into two interrelated subtasks, namely HE extraction and TER extraction. The former subtask is to distinguish all head-entities that may be involved with target relations, and the latter is to identify correspond- ing tail-entities and relations for each extracted head-entity. Next, these two subtasks are further deconstructed into several sequence la- beling problems based on our proposed span-based tagging scheme, which are conveniently solved by a hierarchical boundary tagger and a multi-span decoding algorithm. Owing to the reasonable decomposition strategy, our model can fully capture the semantic interdependency between different steps, as well as reduce noise from irrelevant entity pairs. Experimental results show that our method outperforms previous work by 5.2%, 5.9% and 21.5% (F1 score), achieving a new state-of-the-art on three public datasets.

总结和评论

• 本文的将三元组提取分成了两步：第一步是确定头实体，第二步是确定尾实体和他们的关系。而在确定实体时，用两个序列：头序列和尾序列来确定实体位置——即判断每个词是否可能是实体头或实体尾。最后提取关系时利用确定的头实体和尾实体以及全局信息来进行。
• 整个文章的缺点比较明显：过于依赖头实体的结果。
• 本文是我看到的第一个使用这种先确定头实体，再确定尾实体和关系思路的文章，在这个文章基础上后续有很多工作对其进行了改进。

论文地址：https://ecai2020.eu/papers/615_paper.pdf

概念地图