Summary of Llm Vs. Lawyers: Identifying a Subset Of Summary Judgments in a Large Uk Case Law Dataset, by Ahmed Izzidien and Holli Sargeant and Felix Steffek
LLM vs. Lawyers: Identifying a Subset of Summary Judgments in a Large UK Case Law Dataset
by Ahmed Izzidien, Holli Sargeant, Felix Steffek
First submitted to arxiv on: 4 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Information Retrieval (cs.IR); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel study addresses the challenge of efficiently identifying datasets of court decisions related to a specific legal issue by introducing two computational methods: a traditional natural language processing-based approach leveraging expert-generated keywords and logical operators, and an innovative application of the Claude 2 large language model to classify cases based on content-specific prompts. The authors use the Cambridge Law Corpus of UK court decisions and find that the large language model achieves a weighted F1 score of 0.94 versus 0.78 for keywords. This study marks a pioneering step in employing advanced natural language processing to tackle core legal research tasks, demonstrating how these technologies can bridge systemic gaps and enhance the accessibility of legal information. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A team of researchers worked on a big problem: finding specific court decisions that are related to a certain legal issue. They created two new ways to do this using computers. One way uses expert knowledge and special rules to find the right cases, while the other way uses a super smart language model to read through many cases quickly and accurately. The team tested these methods on a huge collection of UK court decisions and found that the language model was much better at finding the right cases. This breakthrough can help make legal information more accessible and easier to understand. |
Keywords
* Artificial intelligence * Claude * F1 score * Language model * Large language model * Natural language processing
