Call for Papers: LVI 2013: Law via the Internet Conference

The call for papers and presentation proposals has been issued for LVI 2013: Law via the Internet Conference, to be held 26-27 September 2013 on the Channel Island of Jersey.

The conference Website does not seem to state the deadline for submitting papers or proposals. If you know the submission deadline, please feel free to tell us in the comments to this post.

[UPDATE 11 February 2013: The conference organizers now say the submission deadline is 31 March 2013.]

Papers are invited on the topics covered by any of the seven tracks in which the conference program is divided:

• E-Learning: distance, blended, open, mobile, gaming, MOOCing and more?
• Online legal information – starting from scratch
• Legal knowledge in the age of the semantic web
• Communicating our work: journals, blogs and other ways of publishing about open access
• Privacy v open government in legal publishing
• Emerging patterns of information access and usage
• Technological development and free access to law

The conference Twitter account is @JerseyLVI2013 and the conference hashtag is #lvi2013

For details about the tracks, please see the track Websites.

For more details about the conference, please see the conference Website.

Lesmo, Mazzei, Palmirani, and Radicioni on an NLP System for Extracting Legal Modificatory Provisions

Professor Dr. Monica Palmirani of Università di Bologna Dipartimento di Scienze Giuridiche «Antonio Cicu» and CIRSFID, and Professor Dr. Leonardo Lesmo, Dr. Alessandro Mazzei, and Dr. Daniele P. Radicioni, all of Universita’ di Torino Dipartimento di Informatica, have published TULSI: an NLP system for extracting legal modificatory provisions, forthcoming in Artificial Intelligence and Law.

Here is the abstract:

In this work we present the TULSI system (so named after Turin University Legal Semantic Interpreter), a system to produce automatic annotations of normative documents through the extraction of modificatory provisions. TULSI relies on a deep syntactic analysis and a shallow semantic interpreter that are illustrated in detail. We report the results of an experimental evaluation of the system and discuss them, also suggesting future directions for further improvement.

Quaresma on Legal Information Extraction ← Machine Learning Algorithms + Linguistic Information

Professor Dr. Paulo Quaresma of Universidade de Évora Departamento de Informática has published Legal Information Extraction ← Machine Learning Algorithms + Linguistic Information, in LREC 2012 Conference Proceedings: Semantic Processing of Legal Texts (SPLeT-2012) Workshop, pp. 37-38.

Here is the abstract:

In order to automatically extract information from legal texts we propose the use of a mixed approach, using linguistic information and machine learning techniques. In the proposed architecture, lexical, syntactical, and semantical information is used as input for specialized machine learning algorithms, such as support vector machines. This approach was applied to collections of legal documents and the preliminary results were quite promising.

Call for Participation: First Shared Task on Dependency Parsing of Legal Texts, SPLeT 2012

A call for participation — with registration deadline of 30 January 2012 — has been issued for the First Shared Task on Dependency Parsing of Legal Texts, part of SPLeT 2012: The “Semantic Processing of Legal Texts” Workshop, to be held 27 May 2012, in Istanbul, Turkey. (SPLeT 2012 is being held in conjunction with LREC-2012: The Eighth International Conference on Language Resources and Evaluation.)

According to the call:

[T]he goal of the shared task at SPLeT 2012 is to provide common and consistent task definitions and evaluation criteria for dependency parsing of legal texts in order to identify specific challenges posed by the analysis of this type of texts, to obtain a clearer idea of the current state-of-the-art, and to develop and share multilingual domain specific resources.

The languages dealt with will be English and Italian. Participants are expected to submit parsing results for at least one of the two languages involved, but they are strongly encouraged to submit results for both languages.

The task will be organized into two subtasks:

• a basic subtask (mandatory) focusing on dependency parsing of legal texts, aimed at testing the performance of general parsing systems on legal texts;
• a more challenging subtask (optional) focusing on the adaptation of general purpose dependency parsers to the legal domain, aimed at investigating methods and techniques for automatically extracting knowledge from large unlabelled target domain corpora to improve the performance of general parsing systems on legal texts.

For all deadlines, and for other information, please see the call for participation.

HT Dr. Giulia Venturi.

JURIX 2011: Accepted Papers

Accepted papers have been announced for JURIX 2011: The International Conference on Legal Knowledge and Information Systems, to be held 14-16 December 2011, at the University of Vienna Centre for Legal Informatics, in Vienna, Austria.

Wyner on Textual Information Extraction and Ontologies for Legal Case-Based Reasoning

Dr. Adam Wyner of the University of Leeds Centre for Digital Citizenship has posted slides from his recent presentation entitled Textual Information Extraction and Ontologies for Legal Case-Based Reasoning, given 10 November 2010 at the ISKO UK panel Legal Know-How: Organization and Semantic Analysis, held at University College London. Here is the abstract:

This talk gives a brief overview of current developments and prospects in two related areas of the legal semantic web for legal cases – textual information extraction and ontologies. Textual information extraction is a process of automatically annotating and extracting textual information from the legal case base (precedents), thereby identifying elements such as participants, the roles the participants play, the factors which were considered in arriving at a decision, and so on. The information is valuable not only for search (to find applicable precedents), but also to populate an ontology for legal case-based reasoning. An ontology is a formal representation of key aspects of the knowledge of legal professionals with which we can reason (e.g. given an assertion that something is a legal case, we can infer other properties) and with respect to which we can write rules (e.g. reasoning using case factors to arrive at a legal decision). Since it is expensive to manually populate an ontology (meaning to read cases and input the data into the ontology), we use textual information extraction to automatically populate the ontology. We conclude with an appeal for open source, collaborative development of legal knowledge systems among partners in academia, industry, and government.

More information is available on Dr. Wyner’s blog, Language, Logic, Law, Software.

Click here for abstracts and some slides of the other panel presentations.

Saravanan & Ravindran on Identification of Rhetorical Roles for Segmentation and Summarization of a Legal Judgment

M. Saravanan and Professor Balaraman Ravindran, both of the Department of Computer Science and Engineering of the Indian Institute of Technology Madras, have published Identification of Rhetorical Roles for Segmentation and Summarization of a Legal Judgment, forthcoming in Artificial Intelligence and Law. Here is the abstract:

Legal judgments are complex in nature and hence a brief summary of the judgment, known as a headnote, is generated by experts to enable quick perusal. Headnote generation is a time consuming process and there have been attempts made at automating the process. The difficulty in interpreting such automatically generated summaries is that they are not coherent and do not convey the relative relevance of the various components of the judgment. A legal judgment can be segmented into coherent chunks based on the rhetorical roles played by the sentences. In this paper, a comprehensive system is proposed for labeling sentences with their rhetorical roles and extracting structured head notes automatically from legal judgments. An annotated data set was created with the help of legal experts and used as training data. A machine learning technique, Conditional Random Field, is applied to perform document segmentation by identifying the rhetorical roles. The present work also describes the application of probabilistic models for the extraction of key sentences and composing the relevant chunks in the form of a headnote. The understanding of basic structures and distinct segments is shown to improve the final presentation of the summary. Moreover, by adding simple additional features the system can be extended to other legal sub-domains. The proposed system has been empirically evaluated and found to be highly effective on both the segmentation and summarization tasks. The final summary generated with underlying rhetorical roles improves the readability and efficiency of the system.

Fersini et al. on Multimedia Summarization in Law Courts: An Environment for Browsing and Consulting

Elisabetta Fersini of Consorzio Milano Ricerche, and colleagues, have published Multimedia Summarization in Law Courts: An Environment for Browsing and Consulting, in ICT4JUSTICE 2009: Proceedings of the 2nd International Conference on ICT Solutions for Justice, Skopje, FYR Macedonia, September 24, 2009 73-80 (George Eleftherakis and Tom van Engers eds., 2009).

Here is the abstract of the paper:

Digital videos represent a fundamental informative source of those events that occur during a penal proceedings, which thanks to the technologies available nowadays, can be stored, organized and retrieved in short time and with low cost. Considering the dimension that a video source can assume with respect to a courtroom recording, various necessities have been highlighted by the main judicial actors: fast navigation of the stream, efficient access to data inside and effective representation of relevant contents. One of the possible solutions to these requirements is represented by multimedia summarization aimed at deriving a synthetic representation of audio/video contents, characterized by a limited loss of meaningful information. In this paper a multimedia summarization environment is proposed for defining a storyboard for proceedings celebrated into courtrooms.

Francesconi on Legal Rules Learning Based on a Semantic Model for Legislation

Professor Enrico Francesconi of Università degli Studi di Firenze Dipartimento di Sistemi e Informatica and ITTIG/CNR will present a paper entitled Legal Rules Learning Based on a Semantic Model for Legislation (for the full text of the paper, click here for the conference proceedings in PDF and scroll down to the page numbered 46) at SPLeT 2010: The 3rd Workshop on Semantic Processing of Legal Texts, to be held 23 May 2010 in Malta.

The workshop is part of LREC 2010: The 7th International Conference on Language Resources and Evaluation.

Here is the abstract of the paper:

Legal rules extraction from legislative texts can be an effective method to make it easier the implementation of rules-based systems for legal assessment and reasoning, as well as for implementing advanced search and retrieval systems for legislative documents. In this paper machine learning and NLP techniques are used for extracting legal rules on the basis of a semantic model for legislative texts, which is oriented to knowledge reusability and sharing. Moreover the identified entities of the regulated domain can be a starting point to a bottom-up implementation of domain ontologies. This approach is aimed at giving a contribution to bridge the gap between consensus and authoritativeness in legal knowledge representation.

Maarek on the Extraction of Decisions and Contributions from Summaries of French Legal IT Contract Cases

Dr. Manuel Maarek of INRIA Grenoble Rhône-Alpes, LICIT, will present a paper entitled On the Extraction of Decisions and Contributions from Summaries of French Legal IT Contract Cases (for the full text of the paper, click here for the conference proceedings in PDF and scroll down to the page numbered 30) at SPLeT 2010: The 3rd Workshop on Semantic Processing of Legal Texts, to be held 23 May 2010 in Malta.

The workshop is part of LREC 2010: The 7th International Conference on Language Resources and Evaluation.

Here is the abstract of the paper:

French court decisions play an ambivalent role of being the main source for software contract drafters and in the meantime an unreliable legal authority as precedents are not creating laws in the French legal system. Nevertheless, in the legally yet unsettled domain of IT contracts, case decisions are the main source of legal information for contractors. Thus, semantic extraction from French legal IT contract cases could highlight valuable information. We have experimented the extraction of decisions and contributions from a set of summaries of French legal IT contract cases. We are reporting on the ongoing development of our method to represent and infer such semantic knowledge from legal summaries.