构建系统自动提取庇护申请中影响可信度判断的关键信息。
QUEST: A Query and Extraction System for Topics in Asylum Law Application Decisions

- 将可信度分析转化为信息检索任务,结合生成查询与主题抽取。
- 在丹麦庇护上诉数据集上验证,识别可信度因素效果有限。
- 提出基于可信度的新评估方式,适配法律文本分析场景。
庇护申请的法律决定文件内容冗长复杂,包含申请人访谈记录、原始裁决及补充材料。若申请被拒,上诉处理中的关键问题是:原始申请中信息的可信度是否影响了裁决结果。本文提出QUEST系统(查询与提取系统),用于在两个丹麦庇护上诉数据集中提取与可信度评估相关的因素。QUEST将该问题建模为信息检索任务,融合合成查询生成、主题抽取与相关性评估,识别上诉委员会材料中与可信度指标相关的内容。除标准检索评估指标外,我们还提出一种不同于传统相关性的领域特定评估方法,用于衡量系统在可信度因素上的表现。结果表明,使用基于可信度的相关性评估时性能评估更具挑战性,凸显该任务的难度。
原文摘要 · Abstract (English)
Legal decisions on asylum applications consist of long, complex, and heterogeneous documents, covering narrative applicant interviews, original decisions, and additional supporting materials. If an application is rejected, a critical question in processing an appeal is whether the credibility of the information in the original application was a factor that determined the original decision. In this paper, we present the QUEST system (Query and Extraction System for Topics) to extract and identify factors relating to credibility assessments in two datasets of Danish asylum application appeals. QUEST frames this problem as an information retrieval task, combining synthetic query generation, topic extraction, and relevance assessment to identify information related to credibility indicators in appeals board application materials. In addition to standard retrieval evaluation metrics, we propose a new type of domain-specific assessments distinct from the traditional relevance to evaluate the performance of the tested systems with respect to credibility factors. In this way, we obtain insights about how well automatic methods can return answers for different types of indicators appearing in asylum appeals. Our results indicate that there is an increased challenge when estimating performance using credibility-based relevance assessments, thus pointing to the difficulty of the task.
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