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arXiv · 2006.01969

REL: An Entity Linker Standing on the Shoulders of Giants

Johannes M. van Hulst·Faegheh Hasibi·Koen Dercksen·Krisztian Balog·Arjen P. de Vries
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Abstract

Entity linking is a standard component in modern retrieval system that is often performed by third-party toolkits. Despite the plethora of open source options, it is difficult to find a single system that has a modular architecture where certain components may be replaced, does not depend on external sources, can easily be updated to newer Wikipedia versions, and, most important of all, has state-of-the-art performance. The REL system presented in this paper aims to fill that gap. Building on state-of-the-art neural components from natural language processing research, it is provided as a Python package as well as a web API. We also report on an experimental comparison against both well-established systems and the current state-of-the-art on standard entity linking benchmarks.

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Johannes M. van Hulst, Faegheh Hasibi, Koen Dercksen, Krisztian Balog, Arjen P. de Vries. 2020-06-02. REL: An Entity Linker Standing on the Shoulders of Giants. https://doi.org/10.1145/3397271.3401416

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