“篇章共指体现篇章概念的动态转移,成为近年研究热点。本文在梳理共指理论研究的基础上,综述了相关语料库及解析方法,发现共指语料库仍存在以下两个问题:共指关系标注粗疏与基本不考虑整句语义表示的融合。本文以句子级语义标注体系(中文抽象语义表示)为基础构建篇章共指体系,构建了 100 篇共指语料库。本体系涵盖 52 种句内语义关系和 8 种篇章共指关系,二者相结合构建的篇章共指语义图,为篇章级语义分析提供新的框架和数据资源。”

“Abstract Meaning Representation has become a key research area in sentence-level semantic parsing within natural language processing. Substantial progress has been achieved in various NLP tasks using AMR. This paper presents the fourth Chinese Abstract Meaning Representation parsing evaluation, held during the technical evaluation task workshop at CCL 2024. The evaluation also introduced a new test set comprising Ancient Chinese sentences. Results indicated decent performance, with the top team achieving an F1 of 0.8382 in the open modality, surpassing the previous record at CoNLL 2020 by 3.30 percentage points under the MRP metric. However, current large language models perform poorly in AMR parsing of Ancient Chinese, highlighting the need for effective training strategies. The complex syntax and semantics of Ancient Chinese pose significant challenges. Additionally, optimizing transfer learning techniques to better apply knowledge from Chinese Mandarin to Ancient Chinese parsing is crucial. Only through continuous innovation and collaboration can significant advancements in both Ancient Chinese and Chinese Mandarin AMR parsing be achieved.”