LegalEval-2023 Task-6C nclu_team submissions code

Installation

pip install -r dependencies.txt

Fist step is to adopt inut processing, provided in:

• input_orig_convert.py -- original texts
• input_v1_convert.py -- text processor which discards duplicated sentences mentioned simultaneously in both classes (by thanet-m)
• input_v2_convert.py -- text processor which reduce non semantic oriented sentences (v2).

We provide cnn and att-cnn models from AREnets.

Language models implementation provided in a form of the jupyter notebooks.

Projects

• AREnets project

Reference

@article{rusnachenko2023ncluteam,
  title={nclu\_team at SemEval-2023 Task 6C1 and 6C2: Attention-based Approaches for Large Court Judgement Prediction with Explanation},
  author={Nicolay, Rusnachenko and Thanet, Markchom and Huizhi, Liang},
  booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
  month = jul,
  year = "2023",
  address = "Toronto, Canada",
  publisher = "Association for Computational Linguistics"
}