Collaborative System for Question Answering in German Case Law Documents

被引：3

作者：

Hoppe, Christoph ^{[1
]}

Migenda, Nico ^{[1
]}

Pelkmann, David ^{[1
]}

Hoette, Daniel ^{[2
]}

Schenck, Wolfram ^{[1
]}

机构：

[1] Bielefeld Univ Appl Sci, Ctr Appl Data Sci, Gutersloh, Germany

[2] Bielefeld Univ Appl Sci, Fac Business, Bielefeld, Germany

来源：

COLLABORATIVE NETWORKS IN DIGITALIZATION AND SOCIETY 5.0, PRO-VE 2022 | 2022年 / 662卷

关键词：

Question answering; Information retrieval; Human-AI interface design; AI-supported decision making; Legal research;

D O I：

10.1007/978-3-031-14844-6_24

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Legal systems form the foundation of democratic states. Nevertheless, it is nearly impossible for individuals to extract specific information from comprehensive legal documents. We present a human-centered and AI-supported system for semantic question answering (QA) in the German legal domain. Our system is built on top of human collaboration and natural language processing (NLP)-based legal information retrieval. Laypersons and legal professionals re ceive information supporting their research and decision-making by collaborating with the system and its underlying AI methods to enable a smarter society. The internal AI is based on state-of-the-art methods evaluating complex search terms, considering words and phrases specific to German law. Subsequently, relevant documents or answers are ranked and graphically presented to the human. In addition to the novel system, we publish the first annotated data set for QA in the German legal domain. The experimental results indicate that our semantic QA workflow outperforms existing approaches.

引用

页码：303 / 312

页数：10

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