Find Precedents

Multi-factor similarity search using provision overlap, semantic similarity, and outcome alignment.

Select Source Case
Source Case: Providing Incomplete, Self-Serving Advice

Case Number: 22-9

Year: 2022

Found 10 Precedents

Ranked by weighted similarity score
Matching Methods:
Cosine Semantic embedding similarity Jaccard Set intersection / union Categorical Exact match scoring
Similarity Components
Facts Similarity Cosine
58%
Discussion Similarity Cosine
56%
Provision Overlap Jaccard
12%
Outcome Match Categorical
100%
Subject Tags Jaccard
14%
Principle Tensions Jaccard
0%
What They Share

Provisions: II.5.b

Topics: Political Contributions, Gifts, Commissions

Outcome: Both Mixed

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
66%
Discussion Similarity Cosine
61%
Provision Overlap Jaccard
0%
Outcome Match Categorical
50%
Subject Tags Jaccard
14%
Principle Tensions Jaccard
0%
What They Share

Topics: Misrepresentation/Omission of Facts

Outcome: None vs Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
58%
Discussion Similarity Cosine
52%
Provision Overlap Jaccard
11%
Outcome Match Categorical
50%
Subject Tags Jaccard
18%
Principle Tensions Jaccard
0%
What They Share

Provisions: II.3.a

Topics: Professional Reports, Statements, Testimony Misrepresentation/Omission of Facts

Citations: Case 99-8

Outcome: None vs Unethical

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
38%
Discussion Similarity Cosine
47%
Provision Overlap Jaccard
0%
Outcome Match Categorical
100%
Subject Tags Jaccard
9%
Principle Tensions Jaccard
0%
What They Share

Topics: Public Statements and Criticism

Outcome: Both Mixed

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
48%
Discussion Similarity Cosine
55%
Provision Overlap Jaccard
10%
Outcome Match Categorical
50%
Subject Tags Jaccard
21%
Principle Tensions Jaccard
0%
What They Share

Provisions: II.3.a

Topics: Public Statements and Criticism Misrepresentation/Omission of Facts Professional Reports, Statements, Testimony

Outcome: None vs Ethical

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
61%
Discussion Similarity Cosine
59%
Provision Overlap Jaccard
0%
Outcome Match Categorical
50%
Subject Tags Jaccard
14%
Principle Tensions Jaccard
0%
What They Share

Topics: Public Statements and Criticism

Outcome: None vs Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
58%
Discussion Similarity Cosine
56%
Provision Overlap Jaccard
0%
Outcome Match Categorical
50%
Subject Tags Jaccard
22%
Principle Tensions Jaccard
0%
What They Share

Topics: Public Statements and Criticism Misrepresentation/Omission of Facts

Outcome: None vs Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
57%
Discussion Similarity Cosine
59%
Provision Overlap Jaccard
0%
Outcome Match Categorical
50%
Subject Tags Jaccard
11%
Principle Tensions Jaccard
0%
What They Share

Topics: Public Statements and Criticism

Citations: Case 95-5

Outcome: None vs Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
57%
Discussion Similarity Cosine
57%
Provision Overlap Jaccard
0%
Outcome Match Categorical
50%
Subject Tags Jaccard
11%
Principle Tensions Jaccard
0%
What They Share

Topics: Public Statements and Criticism

Outcome: None vs Unethical

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
66%
Discussion Similarity Cosine
56%
Provision Overlap Jaccard
0%
Outcome Match Categorical
50%
Subject Tags Jaccard
0%
Principle Tensions Jaccard
0%
What They Share

Topics: Public Statements and Criticism

Outcome: None vs Ethical

Pattern: Stalemate vs Transfer

References View all

Richter, M.M. & Weber, R.O. (2013). Case-Based Reasoning: A Textbook. Springer. ISBN: 978-3-642-40166-4.

Reimers, N. & Gurevych, I. (2019). Sentence-BERT: Sentence embeddings using Siamese BERT-Networks. Proceedings of EMNLP-IJCNLP 2019, pp. 3982-3992. DOI: 10.18653/v1/D19-1410

Sun, Z., Zhang, K., Yu, W., Wang, H. & Xu, J. (2024). Logic rules as explanations for legal case retrieval. Proceedings of LREC-COLING 2024, pp. 10747-10759. ACL Anthology

Wiratunga, N., et al. (2024). CBR-RAG: Case-based reasoning for retrieval augmented generation in LLMs for legal question answering. arXiv preprint arXiv:2404.04302. arXiv