Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language

Fuente: arXiv
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Main Authors: Shalumov, Vitaly, Haskey, Harel, Solaz, Yuval
Format: Preprint
Published: 2024
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author Shalumov, Vitaly
Haskey, Harel
Solaz, Yuval
author_facet Shalumov, Vitaly
Haskey, Harel
Solaz, Yuval
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_09719
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language
Shalumov, Vitaly
Haskey, Harel
Solaz, Yuval
Computation and Language
Artificial Intelligence
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.
title Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2403.09719