---
license: apache-2.0
datasets:
- opennyaiorg/InRhetoricalRoles
language:
- en
---

# Github
The model can be accessed via our library: [https://github.com/OpenNyAI/Opennyai](https://github.com/OpenNyAI/Opennyai)

# Paper details
[Corpus for Automatic Structuring of Legal Documents](https://aclanthology.org/2022.lrec-1.470)
[Arxiv](https://arxiv.org/abs/2201.13125)

## Author - Publication

```
@InProceedings{kalamkar-EtAl:2022:LREC,
  author    = {Kalamkar, Prathamesh  and  Tiwari, Aman  and  Agarwal, Astha  and  Karn, Saurabh  and  Gupta, Smita  and  Raghavan, Vivek  and  Modi, Ashutosh},
  title     = {Corpus for Automatic Structuring of Legal Documents},
  booktitle      = {Proceedings of the Language Resources and Evaluation Conference},
  month          = {June},
  year           = {2022},
  address        = {Marseille, France},
  publisher      = {European Language Resources Association},
  pages     = {4420--4429},
  abstract  = {In populous countries, pending legal cases have been growing exponentially. There is a need for developing techniques for processing and organizing legal documents. In this paper, we introduce a new corpus for structuring legal documents. In particular, we introduce a corpus of legal judgment documents in English that are segmented into topical and coherent parts. Each of these parts is annotated with a label coming from a list of pre-defined Rhetorical Roles. We develop baseline models for automatically predicting rhetorical roles in a legal document based on the annotated corpus. Further, we show the application of rhetorical roles to improve performance on the tasks of summarization and legal judgment prediction. We release the corpus and baseline model code along with the paper.},
  url       = {https://aclanthology.org/2022.lrec-1.470}
}

```