Kevin Pech


pdf bib
ManyEnt: A Dataset for Few-shot Entity Typing
Markus Eberts | Kevin Pech | Adrian Ulges
Proceedings of the 28th International Conference on Computational Linguistics

We introduce ManyEnt, a benchmark for entity typing models in few-shot scenarios. ManyEnt offers a rich typeset, with a fine-grain variant featuring 256 entity types and a coarse-grain one with 53 entity types. Both versions have been derived from the Wikidata knowledge graph in a semi-automatic fashion. We also report results for two baselines using BERT, reaching up to 70.68% accuracy (10-way 1-shot).