In this work we present an entity linker for DBLP's 2025 version of RDF-based Knowledge Graph. Compared to the 2022 version, DBLP now considers publication venues as a new entity type called dblp:Stream. In the earlier version of DBLPLink, we trained KG-embeddings and re-rankers on a dataset to produce entity linkings. In contrast, in this work, we develop a zero-shot entity linker using LLMs using a novel method, where we re-rank candidate entities based on the log-probabilities of the "yes" token output at the penultimate layer of the LLM.
翻译:本研究提出了一种针对DBLP 2025版基于RDF的知识图谱的实体链接器。相较于2022版,DBLP现引入名为dblp:Stream的新型实体类型以表征出版场所。在早期DBLPLink版本中,我们通过在数据集上训练知识图谱嵌入与重排序器来生成实体链接。与之相对,本研究基于大语言模型开发了零样本实体链接器,采用创新方法通过大语言模型倒数第二层输出的“是”标记的对数概率对候选实体进行重排序。