Gayle McElvain, George Sanchez, Don Teo, Tonya Custis
{"title":"Non-factoid Question Answering in the Legal Domain","authors":"Gayle McElvain, George Sanchez, Don Teo, Tonya Custis","doi":"10.1145/3331184.3331431","DOIUrl":null,"url":null,"abstract":"Non-factoid question answering in the legal domain must provide legally correct, jurisdictionally relevant, and conversationally responsive answers to user-entered questions. We present work done on a QA system that is entirely based on IR and NLP, and does not rely on a structured knowledge base. Our system retrieves concise one-sentence answers for basic questions about the law. It is not restricted in scope to particular topics or jurisdictions. The corpus of potential answers contains approximately 22M documents classified to over 120K legal topics.","PeriodicalId":20700,"journal":{"name":"Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval","volume":"60 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3331184.3331431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Non-factoid question answering in the legal domain must provide legally correct, jurisdictionally relevant, and conversationally responsive answers to user-entered questions. We present work done on a QA system that is entirely based on IR and NLP, and does not rely on a structured knowledge base. Our system retrieves concise one-sentence answers for basic questions about the law. It is not restricted in scope to particular topics or jurisdictions. The corpus of potential answers contains approximately 22M documents classified to over 120K legal topics.