In the PDTB-3, several thousand implicit discourse relations were newly
annotated \textit{within} individual sentences, adding to the over 15,000
implicit relations annotated \textit{across} adjacent sentences in the PDTB-2.
Given that the position of the arguments to these \textit{intra-sentential
implicits} is no longer as well-defined as with \textit{inter-sentential
implicits}, a discourse parser must identify both their location and their
sense. That is the focus of the current work. The paper provides a
comprehensive analysis of our results, showcasing model performance under
different scenarios, pointing out limitations and noting future directions.

本文主要研究 PDTB-3 中数千种隐含话语关系的识别，特别是在句内隐含话语关系的识别和确定，并提出了基于模型的解决方案，并在不同情形下验证了模型性能，指出了局限性并探讨了未来的研究方向。

重新审视 PDTB-3 中的浅层篇章分析：处理句内隐含内容

Revisiting Shallow Discourse Parsing in the PDTB-3: Handling Intra-sentential Implicits

We have developed a full discourse parser in the Penn Discourse Treebank
(PDTB) style. Our trained parser first identifies all discourse and
non-discourse relations, locates and labels their arguments, and then
classifies their relation types. When appropriate, the attribution spans to
these relations are also determined. We present a comprehensive evaluation from
both component-wise and error-cascading perspectives.

我们开发了一种全面的 Penn Discourse Treebank 风格的语篇解析器，它可以识别所有的语篇和非语篇关系，标定它们的参数，并对它们进行关系分类，同时还可以确定适当的属性范围，我们从组件和错误级联的角度进行了综合评估。