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Proceedings of the Natural Legal Language Processing Workshop 2019最新文献

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Developing and Orchestrating a Portfolio of Natural Legal Language Processing and Document Curation Services 发展和编排自然法律语言处理和文件管理服务的组合
Proceedings of the Natural Legal Language Processing Workshop 2019 Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-2207
Georg Rehm, J. Moreno-Schneider, Jorge Gracia, Artem Revenko, V. Mireles, Maria Khvalchik, Ilan Kernerman, Andis Lagzdins, Marcis Pinnis, Artus Vasilevskis, Elena Leitner, J. Milde, Pia Weissenhorn
{"title":"Developing and Orchestrating a Portfolio of Natural Legal Language Processing and Document Curation Services","authors":"Georg Rehm, J. Moreno-Schneider, Jorge Gracia, Artem Revenko, V. Mireles, Maria Khvalchik, Ilan Kernerman, Andis Lagzdins, Marcis Pinnis, Artus Vasilevskis, Elena Leitner, J. Milde, Pia Weissenhorn","doi":"10.18653/v1/W19-2207","DOIUrl":"https://doi.org/10.18653/v1/W19-2207","url":null,"abstract":"We present a portfolio of natural legal language processing and document curation services currently under development in a collaborative European project. First, we give an overview of the project and the different use cases, while, in the main part of the article, we focus upon the 13 different processing services that are being deployed in different prototype applications using a flexible and scalable microservices architecture. Their orchestration is operationalised using a content and document curation workflow manager.","PeriodicalId":224074,"journal":{"name":"Proceedings of the Natural Legal Language Processing Workshop 2019","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130650928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Scalable Methods for Annotating Legal-Decision Corpora 法律决策语料库标注的可扩展方法
Proceedings of the Natural Legal Language Processing Workshop 2019 Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-2202
L. Ferro, J. Aberdeen, K. Branting, Craig Pfeifer, A. Yeh, A. Chakraborty
{"title":"Scalable Methods for Annotating Legal-Decision Corpora","authors":"L. Ferro, J. Aberdeen, K. Branting, Craig Pfeifer, A. Yeh, A. Chakraborty","doi":"10.18653/v1/W19-2202","DOIUrl":"https://doi.org/10.18653/v1/W19-2202","url":null,"abstract":"Recent research has demonstrated that judicial and administrative decisions can be predicted by machine-learning models trained on prior decisions. However, to have any practical application, these predictions must be explainable, which in turn requires modeling a rich set of features. Such approaches face a roadblock if the knowledge engineering required to create these features is not scalable. We present an approach to developing a feature-rich corpus of administrative rulings about domain name disputes, an approach which leverages a small amount of manual annotation and prototypical patterns present in the case documents to automatically extend feature labels to the entire corpus. To demonstrate the feasibility of this approach, we report results from systems trained on this dataset.","PeriodicalId":224074,"journal":{"name":"Proceedings of the Natural Legal Language Processing Workshop 2019","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125999108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
The Extent of Repetition in Contract Language 契约语言中的重复程度
Proceedings of the Natural Legal Language Processing Workshop 2019 Pub Date : 1900-01-01 DOI: 10.18653/v1/W19-2203
D. Simonson, Daniel P. Broderick, J. Herr
{"title":"The Extent of Repetition in Contract Language","authors":"D. Simonson, Daniel P. Broderick, J. Herr","doi":"10.18653/v1/W19-2203","DOIUrl":"https://doi.org/10.18653/v1/W19-2203","url":null,"abstract":"Contract language is repetitive (Anderson and Manns, 2017), but so is all language (Zipf, 1949). In this paper, we measure the extent to which contract language in English is repetitive compared with the language of other English language corpora. Contracts have much smaller vocabulary sizes compared with similarly sized non-contract corpora across multiple contract types, contain 1/5th as many hapax legomena, pattern differently on a log-log plot, use fewer pronouns, and contain sentences that are about 20% more similar to one another than in other corpora. These suggest that the study of contracts in natural language processing controls for some linguistic phenomena and allows for more in depth study of others.","PeriodicalId":224074,"journal":{"name":"Proceedings of the Natural Legal Language Processing Workshop 2019","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116733882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Sentence Boundary Detection in Legal Text 法律文本中的句子边界检测
Proceedings of the Natural Legal Language Processing Workshop 2019 Pub Date : 1900-01-01 DOI: 10.18653/v1/W19-2204
George Sanchez
{"title":"Sentence Boundary Detection in Legal Text","authors":"George Sanchez","doi":"10.18653/v1/W19-2204","DOIUrl":"https://doi.org/10.18653/v1/W19-2204","url":null,"abstract":"In this paper, we examined several algorithms to detect sentence boundaries in legal text. Legal text presents challenges for sentence tokenizers because of the variety of punctuations and syntax of legal text. Out-of-the-box algorithms perform poorly on legal text affecting further analysis of the text. A novel and domain-specific approach is needed to detect sentence boundaries to further analyze legal text. We present the results of our investigation in this paper.","PeriodicalId":224074,"journal":{"name":"Proceedings of the Natural Legal Language Processing Workshop 2019","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129618556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 36
Litigation Analytics: Case Outcomes Extracted from US Federal Court Dockets 诉讼分析:从美国联邦法院摘要中提取的案件结果
Proceedings of the Natural Legal Language Processing Workshop 2019 Pub Date : 1900-01-01 DOI: 10.18653/v1/W19-2206
Tom Vacek, Ronald Teo, Dezhao Song, Conner Cowling, Frank Schilder, Timothy Nugent
{"title":"Litigation Analytics: Case Outcomes Extracted from US Federal Court Dockets","authors":"Tom Vacek, Ronald Teo, Dezhao Song, Conner Cowling, Frank Schilder, Timothy Nugent","doi":"10.18653/v1/W19-2206","DOIUrl":"https://doi.org/10.18653/v1/W19-2206","url":null,"abstract":"Dockets contain a wealth of information for planning a litigation strategy, but the information is locked up in semi-structured text. Manually deriving the outcomes for each party (e.g., settlement, verdict) would be very labor intensive. Having such information available for every past court case, however, would be very useful for developing a strategy because it potentially reveals tendencies and trends of judges and courts and the opposing counsel. We used Natural Language Processing (NLP) techniques and deep learning methods allowing us to scale the automatic analysis of millions of US federal court dockets. The automatically extracted information is fed into a Litigation Analytics tool that is used by lawyers to plan how they approach concrete litigations.","PeriodicalId":224074,"journal":{"name":"Proceedings of the Natural Legal Language Processing Workshop 2019","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124598900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Legal Linking: Citation Resolution and Suggestion in Constitutional Law 法律链接:宪法中的引文解决与建议
Proceedings of the Natural Legal Language Processing Workshop 2019 Pub Date : 1900-01-01 DOI: 10.18653/v1/W19-2205
Robert Shaffer, Stephen Mayhew
{"title":"Legal Linking: Citation Resolution and Suggestion in Constitutional Law","authors":"Robert Shaffer, Stephen Mayhew","doi":"10.18653/v1/W19-2205","DOIUrl":"https://doi.org/10.18653/v1/W19-2205","url":null,"abstract":"This paper describes a dataset and baseline systems for linking paragraphs from court cases to clauses or amendments in the US Constitution. We implement a rule-based system, a linear model, and a neural architecture for matching pairs of paragraphs, taking training data from online databases in a distantly-supervised fashion. In experiments on a manually-annotated evaluation set, we find that our proposed neural system outperforms a rules-driven baseline. Qualitatively, this performance gap seems largest for abstract or indirect links between documents, which suggests that our system might be useful for answering political science and legal research questions or discovering novel links. We release the dataset along with the manually-annotated evaluation set to foster future work.","PeriodicalId":224074,"journal":{"name":"Proceedings of the Natural Legal Language Processing Workshop 2019","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129359379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
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