{"title":"Interpreting contracts using english common law rules as stated by Lord Hoffmann","authors":"John Henderson, Trevor J. M. Bench-Capon","doi":"10.1145/3086512.3086522","DOIUrl":"https://doi.org/10.1145/3086512.3086522","url":null,"abstract":"This paper describes a computational procedure for interpreting contracts in accordance with the English common law rules of interpretation of contract as stated by Lord Hoffmann. Our approach makes extensive use of an ontology of legal terms, specialised for the context in which the contract was made. We illustrate the approach using three examples closely based on actual cases decided by Lord Hoffmann.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130628690","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}
C. Pereira, A. Tettamanzi, B. Liao, Alessandra Malerba, A. Rotolo, Leendert van der Torre
{"title":"Combining fuzzy logic and formal argumentation for legal interpretation","authors":"C. Pereira, A. Tettamanzi, B. Liao, Alessandra Malerba, A. Rotolo, Leendert van der Torre","doi":"10.1145/3086512.3086532","DOIUrl":"https://doi.org/10.1145/3086512.3086532","url":null,"abstract":"The interpretation of a norm is often uncertain and conflicting. In this paper we propose a model for arguing about legal interpretation, which considers the problems of vagueness. After motivating our adoption of graded categories as a tool to tackle the problem of open texture in legal interpretation, we introduce a model based on fuzzy logic and argumentation. Then, we conduct a case study by using an example from medically assisted reproduction.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"531 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122505882","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}
Cristian Cardellino, Milagro Teruel, L. A. Alemany, S. Villata
{"title":"A low-cost, high-coverage legal named entity recognizer, classifier and linker","authors":"Cristian Cardellino, Milagro Teruel, L. A. Alemany, S. Villata","doi":"10.1145/3086512.3086514","DOIUrl":"https://doi.org/10.1145/3086512.3086514","url":null,"abstract":"In this paper we try to improve Information Extraction in legal texts by creating a legal Named Entity Recognizer, Classifier and Linker. With this tool, we can identify relevant parts of texts and connect them to a structured knowledge representation, the LKIF ontology. More interestingly, this tool has been developed with relatively little effort, by mapping the LKIF ontology to the YAGO ontology and through it, taking advantage of the mentions of entities in the Wikipedia. These mentions are used as manually annotated examples to train the Named Entity Recognizer, Classifier and Linker. We have evaluated the approach on holdout texts from the Wikipedia and also on a small sample of judgments of the European Court of Human Rights, resulting in a very good performance, i.e., around 80% F-measure for different levels of granularity. We present an extensive error analysis to direct further developments, and we expect that this approach can be successfully ported to other legal subdomains, represented by different ontologies.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131513451","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}
{"title":"The pragmatic oddity in norm-based deontic logics","authors":"X. Parent, Leendert van der Torre","doi":"10.1145/3086512.3086529","DOIUrl":"https://doi.org/10.1145/3086512.3086529","url":null,"abstract":"The ideal worlds of a possible worlds semantics may satisfy both a primary obligation and an associated secondary obligation, for example the obligation to keep a promise and the obligation to apologise for not keeping it. This is known as the pragmatic oddity introduced by Prakken and Sergot. We argue that an adequate treatment of the pragmatic oddity within a norm-based semantics can be obtained, by not allowing primary and secondary obligations to aggregate, because they are obligations of a different kind. On the basis of this conceptual analysis, we introduce two logics, depending on the stance taken on the representation of normative conflicts, and we present sound and complete proof systems for these logics. We then give a formal analysis, discuss extensions, and highlight various topics for further research.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115769599","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}
James O'Neill, P. Buitelaar, Cécile Robin, Leona O'Brien
{"title":"Classifying sentential modality in legal language: a use case in financial regulations, acts and directives","authors":"James O'Neill, P. Buitelaar, Cécile Robin, Leona O'Brien","doi":"10.1145/3086512.3086528","DOIUrl":"https://doi.org/10.1145/3086512.3086528","url":null,"abstract":"Texts expressed in legal language are often difficult and time consuming for lawyers to read through, particularly for the purpose of identifying relevant deontic modalities (obligations, prohibitions and permissions). By nature, the language of law is strict, hence the predominant use of modal logic as a substitute for the syntactical ambiguity in natural language, specifically, deontic and alethic logic for the respective modalities. However, deontic modalities which express obligations, prohibitions and permissions, can have varying degree and preciseness to which they correspond to a matter, strict deontic logic does not allow for such quantitative measures. Therefore, this paper outlines a data-driven approach by classifying deontic modalities using ensembled Artificial Neural Networks (ANN) that incorporate domain specific legal distributional semantic model (DSM) representations, in combination with, a general DSM representation. We propose to use well calibrated probability estimates from these classifiers as an approximation to the degree which an obligation/prohibition or permission belongs to a given class based on SME annotated sentences. Best results show 82.33 % accuracy on a held-out test set.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115866668","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}
Rohan Nanda, Luigi Di Caro, G. Boella, Hristo Konstantinov, Tenyo Tyankov, Daniel Traykov, H. Hristov, F. Costamagna, Llio Humphreys, L. Robaldo, Michele Romano
{"title":"A unifying similarity measure for automated identification of national implementations of european union directives","authors":"Rohan Nanda, Luigi Di Caro, G. Boella, Hristo Konstantinov, Tenyo Tyankov, Daniel Traykov, H. Hristov, F. Costamagna, Llio Humphreys, L. Robaldo, Michele Romano","doi":"10.1145/3086512.3086527","DOIUrl":"https://doi.org/10.1145/3086512.3086527","url":null,"abstract":"This paper presents a unifying text similarity measure (USM) for automated identification of national implementations of European Union (EU) directives. The proposed model retrieves the transposed provisions of national law at a fine-grained level for each article of the directive. USM incorporates methods for matching common words, common sequences of words and approximate string matching. It was used for identifying transpositions on a multilingual corpus of four directives and their corresponding national implementing measures (NIMs) in three different languages : English, French and Italian. We further utilized a corpus of four additional directives and their corresponding NIMs in English language for a thorough test of the USM approach. We evaluated the model by comparing our results with a gold standard consisting of official correlation tables (where available) or correspondences manually identified by domain experts. Our results indicate that USM was able to identify transpositions with average F-score values of 0.808, 0.736 and 0.708 for French, Italian and English Directive-NIM pairs respectively in the multilingual corpus. A comparison with state-of-the-art methods for text similarity illustrates that USM achieves a higher F-score and recall across both the corpora.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124478114","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}
Peter Schmitz, E. Francesconi, Simon-Pierre Landercy, Brahim Batouche, V. Touly
{"title":"A knowledge organization system for e-participation in law-making","authors":"Peter Schmitz, E. Francesconi, Simon-Pierre Landercy, Brahim Batouche, V. Touly","doi":"10.1145/3086512.3086539","DOIUrl":"https://doi.org/10.1145/3086512.3086539","url":null,"abstract":"This paper describes the knowledge organization system developed within a project for e-Participation in the EU law-making process. The project aims to build a web platform allowing citizens and other stakeholders to actively participate in the EU law-making by providing comments and amendments, as well expressing sentiments, on pre-legislative documents. The semantic approach follows a pure RDF(S)/ OWL implementation for all the produced contributions (documents, comments, amendments, statistics), with the aim to made them available as Linked Open Data.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124583499","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}
{"title":"Legal content fusion for legal information retrieval","authors":"Seon-ik Heo, Kihyun Hong, Young-Yik Rhim","doi":"10.1145/3086512.3086549","DOIUrl":"https://doi.org/10.1145/3086512.3086549","url":null,"abstract":"With recent increasing attention to legal information processing, legal information retrieval (IR) has become one of the active research fields. However, there are still many hindrances obtaining rigorous results in legal IR applications in comparison with IR applications for general document retrieval. It is mainly due to the characteristics of legal information such as the complicated structure of legal contents and usage of legal jargon. In this paper, we present a legal IR method, which is a structure-wise IR approach. e presented method in this study focuses on analyzing the contents of legal documents and applying the content contributions to the IR processing. We demonstrate the performance of the proposed IR method with the COILEE data set, which are derived from Japanese bar exams.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114520223","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}
{"title":"Extracting contract elements","authors":"Ilias Chalkidis, Ion Androutsopoulos, A. Michos","doi":"10.1145/3086512.3086515","DOIUrl":"https://doi.org/10.1145/3086512.3086515","url":null,"abstract":"We study how contract element extraction can be automated. We provide a labeled dataset with gold contract element annotations, along with an unlabeled dataset of contracts that can be used to pre-train word embeddings. Both datasets are provided in an encoded form to bypass privacy issues. We describe and experimentally compare several contract element extraction methods that use manually written rules and linear classifiers (logistic regression, SVMs) with hand-crafted features, word embeddings, and part-of-speech tag embeddings. The best results are obtained by a hybrid method that combines machine learning (with hand-crafted features and embeddings) and manually written post-processing rules.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128218888","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}
Latifa Al-Abdulkarim, Katie Atkinson, S. Atkinson, Trevor J. M. Bench-Capon
{"title":"Angelic environment: demonstration","authors":"Latifa Al-Abdulkarim, Katie Atkinson, S. Atkinson, Trevor J. M. Bench-Capon","doi":"10.1145/3086512.3086546","DOIUrl":"https://doi.org/10.1145/3086512.3086546","url":null,"abstract":"A development environment for the Angelic Methodology.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"59 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117221558","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}