# nigam@COLIEE-22: Legal Case Retrieval and Entailment using Cascading of Lexical and Semantic-based models

arXiv: https://arxiv.org/abs/2204.07853 · HTML: https://mlsanity.com/paper/2204.07853/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 11 references that are in the map.
- First posted on arXiv 16 Apr 2022.

## Builds on (most cited first, 4 of 4)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features](https://mlsanity.com/paper/1703.02507/) (2017)
- [Yes, BM25 is a Strong Baseline for Legal Case Retrieval](https://mlsanity.com/paper/2105.05686/) (2021)
- [THUIR@COLIEE-2020: Leveraging Semantic Understanding and Exact Matching for Legal Case Retrieval and Entailment](https://mlsanity.com/paper/2012.13102/) (2020)

## Built on by (most cited first, 9 of 9)

- [THUIR@COLIEE 2023: More Parameters and Legal Knowledge for Legal Case Entailment](https://mlsanity.com/paper/2305.06817/) (2023)
- [Fact-based Court Judgment Prediction](https://mlsanity.com/paper/2311.13350/) (2023)
- [LegalSeg: Unlocking the Structure of Indian Legal Judgments Through Rhetorical Role Classification](https://mlsanity.com/paper/2502.05836/) (2025)
- [Identification of Regulatory Requirements Relevant to Business Processes: A Comparative Study on Generative AI, Embedding-based Ranking, Crowd and Expert-driven Methods](https://mlsanity.com/paper/2401.02986/) (2024)
- [TathyaNyaya and FactLegalLlama: Advancing Factual Judgment Prediction and Explanation in the Indian Legal Context](https://mlsanity.com/paper/2504.04737/) (2025)
- [Segment First, Retrieve Better: Realistic Legal Search via Rhetorical Role-Based Queries](https://mlsanity.com/paper/2508.00679/) (2025)
- [GreekBarRetrieval: A Benchmark for Greek Statutory Retrieval](https://mlsanity.com/paper/2608.18752/) (2026)
- [Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej](https://mlsanity.com/paper/2504.03486/) (2025)
- [UK-PRBENCH: A Paragraph-Level Precedent Retrieval Benchmark for United Kingdom Case Law](https://mlsanity.com/paper/2609.24613/) (2026)

## Abstract (arXiv)

This paper describes our submission to the Competition on Legal Information Extraction/Entailment 2022 (COLIEE-2022) workshop on case law competition for tasks 1 and 2. Task 1 is a legal case retrieval task, which involves reading a new case and extracting supporting cases from the provided case law corpus to support the decision. Task 2 is the legal case entailment task, which involves the identification of a paragraph from existing cases that entails the decision in a relevant case. We employed the neural models Sentence-BERT and Sent2Vec for semantic understanding and the traditional retrieval model BM25 for exact matching in both tasks. As a result, our team ("nigam") ranked 5th among all the teams in Tasks 1 and 2. Experimental results indicate that the traditional retrieval model BM25 still outperforms neural network-based models.