Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines

Łukasz Borchmann, Dawid Wisniewski, Andrzej Gretkowski, Izabela Kosmala, Dawid Jurkiewicz, Łukasz Szałkiewicz, Gabriela Pałka, Karol Kaczmarek, Agnieszka Kaliska, Filip Graliński


Abstract
We propose a new shared task of semantic retrieval from legal texts, in which a so-called contract discovery is to be performed – where legal clauses are extracted from documents, given a few examples of similar clauses from other legal acts. The task differs substantially from conventional NLI and shared tasks on legal information extraction (e.g., one has to identify text span instead of a single document, page, or paragraph). The specification of the proposed task is followed by an evaluation of multiple solutions within the unified framework proposed for this branch of methods. It is shown that state-of-the-art pretrained encoders fail to provide satisfactory results on the task proposed. In contrast, Language Model-based solutions perform better, especially when unsupervised fine-tuning is applied. Besides the ablation studies, we addressed questions regarding detection accuracy for relevant text fragments depending on the number of examples available. In addition to the dataset and reference results, LMs specialized in the legal domain were made publicly available.
Anthology ID:
2020.findings-emnlp.380
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2020
Month:
November
Year:
2020
Address:
Online
Venues:
EMNLP | Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4254–4268
Language:
URL:
https://aclanthology.org/2020.findings-emnlp.380
DOI:
10.18653/v1/2020.findings-emnlp.380
Bibkey:
Cite (ACL):
Łukasz Borchmann, Dawid Wisniewski, Andrzej Gretkowski, Izabela Kosmala, Dawid Jurkiewicz, Łukasz Szałkiewicz, Gabriela Pałka, Karol Kaczmarek, Agnieszka Kaliska, and Filip Graliński. 2020. Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4254–4268, Online. Association for Computational Linguistics.
Cite (Informal):
Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines (Borchmann et al., Findings 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.findings-emnlp.380.pdf
Code
 applicaai/contract-discovery
Data
Contract DiscoveryActivityNetMultiNLISNLI