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.

翻译：本文探讨了梵语知识系统开发中的挑战与机遇，重点关注问答任务。通过提出知识图谱自动构建框架、引入面向本体驱动与通用任务的标注工具，以及提供多样化的网络界面、工具集和软件库，我们在计算梵语领域作出了重要贡献。这些成果不仅提升了梵语文本分析的可访问性与准确性，也为知识表示与语言处理的进一步发展奠定了基础。最终，本研究有助于保存、理解并利用梵语文本所蕴含的丰富语言学信息。