Problem
Research questions and friction points this paper is trying to address.
asylum applications
credibility assessment
legal decisions
information retrieval
appeal processing
QUEST: A Query and Extraction System for Topics in Asylum Law Application Decisions
🤖 AI Summary
为解决难民申请裁决中可信度因素识别问题，QUEST系统通过信息检索、合成查询生成、主题提取及关联性评估方法来处理丹麦难民上诉材料。
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
synthetic query generation
topic extraction
credibility-based relevance assessments
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