We address the challenges and opportunities in the development of knowledge
systems for Sanskrit, with a focus on question answering. By proposing a
framework for the automated construction of knowledge graphs, introducing
annotation tools for ontology-driven and general-purpose tasks, and offering a
diverse collection of web-interfaces, tools, and software libraries, we have
made significant contributions to the field of computational Sanskrit. These
contributions not only enhance the accessibility and accuracy of Sanskrit text
analysis but also pave the way for further advancements in knowledge
representation and language processing. Ultimately, this research contributes
to the preservation, understanding, and utilization of the rich linguistic
information embodied in Sanskrit texts.

通过自动构建知识图谱的框架、引入本体驱动和通用任务的注释工具，以及提供多样化的网页界面、工具和软件库，我们在梵语的知识系统发展中解决了挑战与机遇，尤其在问答方面。这些贡献不仅提高了梵语文本分析的可访问性和准确性，而且为知识表达和语言处理领域的进一步发展铺平了道路。最终，这项研究对于保护、理解和利用梵语文本中所蕴含的丰富语言信息具有重要意义。