Event-Grounded Criminal Court View Generation with Cooperative (Large) Language Models

Core Concepts

The core message of this paper is to propose an Event Grounded Generation (EGG) method for criminal court view generation that incorporates fine-grained event information extracted from case facts using cooperative (large) language models.

Abstract

The paper presents an Event Grounded Generation (EGG) method for criminal court view generation, which consists of two phases:
Extraction Phase:

The authors design a zero-shot LLMs-based event extractor that can extract events from case facts without extensive manual annotation.
Specifically, they fine-tune a LLMs-based QA model on a legal QA dataset (CJRC) and then use it to extract events by prompting with annotated event-related questions for each case type.
This approach only requires annotating around 9 questions per case type, significantly reducing the annotation effort compared to previous methods.
Generation Phase:

The authors employ a PLMs-based court view generator that takes the merged case facts and extracted events as input to generate the court views.
To address the computational burden posed by the use of LLMs in the extraction phase, the authors also propose an LLMs-free EGG method (EGGfree) that eliminates the requirement for event extraction during inference.
EGGfree encodes the fact and event separately and uses a contrastive learning module to help the fact encoder capture co-occurrence signals with the event, allowing it to generate court views based solely on the case fact.
The extensive experiments on a real-world dataset demonstrate the effectiveness of the proposed EGG and EGGfree methods in improving the performance of event extraction and court view generation compared to several competitive baselines.

Stats

Bob and Tom had a verbal altercation while chatting online.
Bob and Tom both led more than ten people to meet at a park and then exchanged blows.
During the fight, Bob was armed with an iron spanner and injured Tom.
Bob compensated Tom's economic loss of $10,000 and obtained Tom's understanding.

Quotes

"Our court hold that Bob and Tom engaged in a verbal dispute and gathered people to fight. During the fight, Bob injured Tom with an iron spanner. However, the court also found that Bob actively compensated Tom for his losses and obtained his understanding, which was considered a mitigating factor according to the law."

Key Insights Distilled From

Event Grounded Criminal Court View Generation withCooperative (Large) Language Models

by Linan Yue,Qi... at arxiv.org 04-11-2024

https://arxiv.org/pdf/2404.07001.pdf

Deeper Inquiries

What are the potential legal implications of the event of Bob and Tom gathering a crowd to fight

The event of Bob and Tom gathering a crowd to fight has several potential legal implications. Firstly, this action could lead to charges related to public order offenses, such as disturbing the peace or inciting violence. Depending on the specific circumstances of the gathering and the resulting altercation, additional charges such as assault, battery, or even manslaughter could be considered. The presence of weapons during the fight, as mentioned in the event, could also lead to charges related to the possession or use of weapons in a criminal act. Furthermore, if any individuals involved in the fight sustained serious injuries or if the altercation resulted in fatalities, the legal implications could escalate to charges of aggravated assault or even murder.

How might the court's consideration of Bob's compensation and Tom's understanding impact the sentencing in this case

The court's consideration of Bob's compensation to Tom and Tom's understanding could impact the sentencing in this case in several ways. Firstly, Bob's act of compensating Tom for his economic loss could be viewed as a mitigating factor by the court. This compensation could demonstrate Bob's remorse, willingness to make amends, and acceptance of responsibility for his actions, potentially leading to a more lenient sentence. Additionally, Tom's understanding of the situation and potential forgiveness towards Bob could also be considered by the court as a mitigating factor. Tom's forgiveness could indicate a desire for reconciliation and could influence the court's decision in terms of sentencing, potentially leading to a more lenient outcome for Bob.

How could the proposed EGG method be extended to generate court views for other types of criminal cases beyond intentional injury

The proposed Event Grounded Generation (EGG) method could be extended to generate court views for other types of criminal cases beyond intentional injury by adapting the event extraction and generation process to suit the specific characteristics of different case types. For example, for cases involving theft, the event extraction phase could focus on identifying key events related to the act of theft, such as the method of theft, the items stolen, and any accomplices involved. The generation phase could then incorporate this extracted event information into the court views to provide a comprehensive summary of the theft case facts and the legal implications for sentencing. By customizing the event extraction questions and incorporating domain-specific knowledge, EGG can be tailored to generate accurate and informative court views for a wide range of criminal case types.