Zvi Kons, Aharon Satt, et al.
ICASSP 2022
We describe a large, high-quality benchmark for the evaluation of Mention Detection tools. The benchmark contains annotations of both named entities as well as other types of entities, annotated on different types of text, ranging from clean text taken from Wikipedia, to noisy spoken data. The benchmark was built through a highly controlled crowd sourcing process to ensure its quality. We describe the benchmark, the process and the guidelines that were used to build it. We then demonstrate the results of a state-of-the-art system running on that benchmark.
Zvi Kons, Aharon Satt, et al.
ICASSP 2022
Marvin Alberts, Teodoro Laino
ACS Fall 2025
David Alvarez-Melis, Youssef Mroueh, et al.
AISTATS 2020
Kofi Arhin, Ioana Baldini Soares, et al.
NeurIPS 2021