RI: Exploiting and Exploring Discourse Connectivity: Deriving New Technology and Knowledge from the Penn Discourse Treebank

大规模的句子级标注语料库在自然语言研究中起着至关重要的作用。它们使统计知识（来自语料库）与语言知识的大规模集成成为可能，从而导致技术和科学应用，例如信息提取、问题回答、摘要和机器翻译等。这种方法现在正被扩展到语篇层面，从而超越了句子层面。利用宾大语篇树库（PDTB）资源，一个用语篇结构和相关语义标注的大型语料库，正在开展新的语篇处理主要实验工作，从而生成更连贯的摘要和文本，提取文本中的复杂关系等，以及与语言技术相关的基础研究。这项工作也为句子层次结构和语篇层次结构之间的关系提供了更深入的理解。在追求这些目标的同时，还在开发各种有效利用PDTB资源的工具。该研究项目还结合了一个强大的教育项目，包括培训PDTB方法的研究人员，以便在与英语有很大差异的其他语言中开发类似的资源。这部分研究项目有国际组成部分，包括与捷克共和国、印度和芬兰的研究小组合作。这项国际合作由美国国家科学基金会国际科学与工程办公室资助。

Large scale corpora annotated at the sentence level have played a critical role in natural language research. They have enabled large scale integration of statistical knowledge (derived from the corpora) with linguistic knowledge leading to both technological and scientific applications, such as information extraction, question answering, summarization, and machine translation, among others. This approach is now being extended to the discourse level, thus going beyond the sentence level. Using a resource called the Penn Discourse Treebank (PDTB), a large scale corpus annotated with discourse structure along with the associated semantics, new major experimental work on discourse processing is being carried out, leading to the generation of more coherent summaries and texts, extraction of complex relations in texts, among others, as well as foundational research relevant to language technology. This work is also providing a deeper understanding of the relationship between sentence level and discourse level structures. While pursuing these goals, a variety of tools for making a productive use of the PDTB resource are also being developed. This research program is also coupled with a strong educational program involving training researchers in the PDTB methodology so that similar resources can be developed in other languages substantially divergent from English. This part of the research program has international components including collaboration with research groups in Czech Republic, India, and Finland. The international collaboration is funded by the NSF Office of International Science and Engineering.