We present the task of Automated Punishment Extraction (APE) in sentencing decisions from criminal court cases in Hebrew. Addressing APE will enable the identification of sentencing patterns and constitute an important stepping stone for many follow up legal NLP applications in Hebrew, including the prediction of sentencing decisions. We curate a dataset of sexual assault sentencing decisions and a manuallyannotated evaluation dataset, and implement rulebased and supervised models. We find that while supervised models can identify the sentence containing the punishment with good accuracy, rulebased approaches outperform them on the full APE task. We conclude by presenting a first analysis of sentencing patterns in our dataset and analyze common models' errors, indicating avenues for future work, such as distinguishing between probation and actual imprisonment punishment. We will make all our resources available upon request, including data, annotation, and first benchmark models.
|Original language||American English|
|Title of host publication||Natural Legal Language Processing, NLLP 2021 - Proceedings of the 2021 Workshop|
|Editors||Nikolaos Aletras, Ion Androutsopoulos, Leslie Barrett, Catalina Goanta, Daniel Preotiuc-Pietro|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||10|
|State||Published - 2021|
|Event||3rd Natural Legal Language Processing, NLLP 2021 - Punta Cana, Dominican Republic|
Duration: 10 Nov 2021 → …
|Name||Natural Legal Language Processing, NLLP 2021 - Proceedings of the 2021 Workshop|
|Conference||3rd Natural Legal Language Processing, NLLP 2021|
|Period||10/11/21 → …|
Bibliographical noteFunding Information:
We thank the anonymous reviewers for their helpful comments and feedback. This work was sup ported in part by a research gift from the Allen Institute for AI and by a research grant from the Center for Interdisciplinary Data Science Research (CIDR) at the Hebrew University of Jerusalem.
© 2021 Association for Computational Linguistics.
- Computation and Language (cs.CL)
- FOS: Computer and information sciences