Entity Linking powered by Graph Embedding
In this talk, i will present a technique for entity linking that employs graph embeddings to perform collective disambiguation.
Weitere Informationen
Entity Linking (EL), the task of mapping ambiguous Named Entities to unique identifiers in a knowledge base, is a cornerstone of multiple Information Retrieval and Text Analysis systems. In this talk, i will present a technique for entity linking that employs graph embeddings to perform collective disambiguation. We implement and evaluate an EL pipeline that uses DBpedia as knowledge base and leverages specific algorithms for fast candidate search and high-performance state-space search optimization. Compared to existing solutions, our approach offers state-of-the-art accuracy on a variety of datasets without any supervised training and provides real-time execution even when processing documents with dozens of Named Entities.
Paper: https://dl.acm.org/citation.cfm?id=3328499
Zielgruppe
Anyone interested in interlinking data
