Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew
  Language
Vitaly Shalumov Harel Haskey Yuval Solaz
In this paper, we introduce summarization MevakerSumm and conclusion
extraction MevakerConc datasets for the Hebrew language based on the State
Comptroller and Ombudsman of Israel reports, along with two auxiliary datasets.
We accompany these datasets with models for conclusion extraction (HeConE,
HeConEspc) and conclusion allocation (HeCross). All of the code, datasets, and
model checkpoints used in this work are publicly available.