Sara Rosenthal, Ken Barker, et al.
EMNLP-IJCNLP 2019
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.
Sara Rosenthal, Ken Barker, et al.
EMNLP-IJCNLP 2019
Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023
Arvind Agarwal, Laura Chiticariu, et al.
NAACL 2021
Alexandre Rademaker, Guilherme Augusto Ferreira Lima, et al.
ICNLSP 2023