用自然语言自动重写SPARQL查询，支持复杂本体对齐。
Enhancing SPARQL Query Rewriting for Complex Ontology Alignments
- 基于等价传递性与大模型能力，自动转换自然语言为SPARQL。
- 首次有效处理复杂本体对齐中的(c:c)映射，提升查询准确率。
- 让不懂SPARQL的用户也能轻松查询异构本体数据。
SPARQL查询重写是统一查询链上数据网络中异构本体的基础机制。然而，本体对齐的复杂性，尤其是丰富的对应关系（c:c），使该过程面临挑战。现有方法主要关注简单（s:s）和部分复杂（s:c）对齐，忽视了更表达性强的对齐带来的难题。此外，SPARQL复杂的语法对非专家用户构成障碍，限制了本体知识的充分利用。本文提出一种创新方法，可根据用户以自然语言表达的需求，自动将源本体的SPARQL查询重写为目标本体。该方法融合等价传递性原理与GPT-4等大语言模型的先进能力，能高效处理复杂对齐，特别是（c:c）对应关系，充分挖掘其表达力。同时，它为不熟悉SPARQL的用户提供灵活的查询途径，促进对齐本体的可访问性。
原文摘要 · Abstract (English)
SPARQL query rewriting is a fundamental mechanism for uniformly querying heterogeneous ontologies in the Linked Data Web. However, the complexity of ontology alignments, particularly rich correspondences (c : c), makes this process challenging. Existing approaches primarily focus on simple (s : s) and partially complex ( s : c) alignments, thereby overlooking the challenges posed by more expressive alignments. Moreover, the intricate syntax of SPARQL presents a barrier for non-expert users seeking to fully exploit the knowledge encapsulated in ontologies. This article proposes an innovative approach for the automatic rewriting of SPARQL queries from a source ontology to a target ontology, based on a user's need expressed in natural language. It leverages the principles of equivalence transitivity as well as the advanced capabilities of large language models such as GPT-4. By integrating these elements, this approach stands out for its ability to efficiently handle complex alignments, particularly (c : c) correspondences , by fully exploiting their expressiveness. Additionally, it facilitates access to aligned ontologies for users unfamiliar with SPARQL, providing a flexible solution for querying heterogeneous data.
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