基于Self-Attention的句法感知汉语框架语义角色标注(Syntax-Aware Chinese Frame Semantic Role Labeling Based on Self-Attention)

no code implementations • CCL 2020 • Xiaohui Wang, Ru Li, Zhiqiang Wang, Qinghua Chai, Xiaoqi Han

框架语义角色标注(Frame Semantic Role Labeling, FSRL)是基于FrameNet标注体系的语义分析任务。语义角色标注通常对句法有很强的依赖性, 目前的语义角色标注模型大多基于双向长短时记忆网络Bi-LSTM, 虽然可以获取句子中的长距离依赖信息, 但无法很好获取句子中的句法信息。因此, 引入self-attention机制来捕获句子中每个词的句法信息。实验结果表明, 该模型在CFN(Chinese FrameNet, 汉语框架网)数据集上的F1达到83. 77%, 提升了近11%。

Semantic Role Labeling

A Knowledge-Guided Framework for Frame Identification

no code implementations • ACL 2021 • Xuefeng Su, Ru Li, XiaoLi Li, Jeff Z. Pan, Hu Zhang, Qinghua Chai, Xiaoqi Han

In this paper, we propose a Knowledge-Guided Frame Identification framework (KGFI) that integrates three types frame knowledge, including frame definitions, frame elements and frame-to-frame relations, to learn better frame representation, which guides the KGFI to jointly map target words and frames into the same embedding space and subsequently identify the best frame by calculating the dot-product similarity scores between the target word embedding and all of the frame embeddings.

Semantic Parsing Sentence

Implicit Role Linking on Chinese Discourse: Exploiting Explicit Roles and Frame-to-Frame Relations

no code implementations • IJCNLP 2015 • Ru Li, Juan Wu, Zhiqiang Wang, Qinghua Chai