1. MELO: An Evaluation Benchmark for Multilingual Entity Linking of Occupations
- Author
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Retyk, Federico, Gasco, Luis, Carrino, Casimiro Pio, Deniz, Daniel, and Zbib, Rabih
- Subjects
Computer Science - Computation and Language - Abstract
We present the Multilingual Entity Linking of Occupations (MELO) Benchmark, a new collection of 48 datasets for evaluating the linking of entity mentions in 21 languages to the ESCO Occupations multilingual taxonomy. MELO was built using high-quality, pre-existent human annotations. We conduct experiments with simple lexical models and general-purpose sentence encoders, evaluated as bi-encoders in a zero-shot setup, to establish baselines for future research. The datasets and source code for standardized evaluation are publicly available at https://github.com/Avature/melo-benchmark, Comment: Accepted to the 4th Workshop on Recommender Systems for Human Resources (RecSys in HR 2024) as part of RecSys 2024
- Published
- 2024