ASAIL 2021

5th Workshop on Automated Semantic Analysis of Information in Legal Text

June 25, 2021

Held online in conjunction with ICAIL 2021

- Call for Papers (extended) -

Extended Paper submission deadline: April 26 May 3, 2021

The Fifth Workshop on Automated Detection, Extraction and Analysis of Semantic Information in Legal Texts (ASAIL) will be held online in conjunction with the 18th International Conference on Artificial Intelligence and Law (ICAIL 2021). It is a continuation of the successful prior ASAIL workshops at ICAIL and Jurix.

This workshop will bring together an interdisciplinary group of scholars, academic and corporate researchers, legal practitioners, and legal service providers for an extended, collaborative discussion about applying natural language processing and machine learning to the semantic analysis of legal texts. Semantic analysis is the process of relating syntactic elements and structures, drawn from the levels of phrases, clauses, sentences, paragraphs, and whole documents, to their language-independent meanings in a given domain, including meanings specific to legal information. The range of focal texts includes:

  • statutes, regulations, and court-made pronouncements of legal rules embodying legal norms;

  • textual arguments in legal case decisions interpreting legal norms and applying them in concrete fact situations;

  • legislative and policy-based debates concerning proposed legal norms, their purpose and meaning;

  • actual and proposed contracts that need to be analyzed for the permissions and obligations they encode and their consistency with organizational preferences or legal frameworks;

  • technical reports and other evidentiary documents;

  • court testimony and narrative texts in submissions by self-represented parties.

Researchers have long been developing tools to aggregate, synthesize, structure, summarize, and reason about legal norms and arguments in texts. Current dramatic advances in natural language processing, text and argument mining, information extraction, and automated question answering are changing how automatic semantic analysis of legal rules and arguments will be performed in the future. In particular, the recent breakthrough in natural language processing brought about by neural network models, including transfer learning using complex language models, has created immense new potential for leveraging legal text for technology supporting legal practice, research, argumentation, and decision making. At the same time, increasing awareness of the mandate of ethical use of AI is fueling a debate about the requirements of such systems and motivates important exploratory work on explainable legal AI.

Covered Topics

  • Application of NLP to analyze arguments in legal texts: identification, annotation, and extraction of argument elements; relating arguments; and classifying arguments

  • Automated or semi-automated approaches to extracting legal norms from legal texts

  • Creation/evaluation of high quality annotated natural language legal corpora

  • Automated semantic analysis of legal texts

  • Development of computer-supported annotation environments for automated semantic analysis of legal texts

  • Applications of machine learning to train automatic systems on tasks related to semantic analysis of legal texts, identifying legal norms, or extracting legal argumentation

  • Summarization, visualization, and information retrieval for legal texts

  • Argument mining of court cases, legislative records, legal policy debates and other legal documents

  • Automated translations of legal text to formal or abstract representations that can be used for reasoning

  • Applications of computational models of legal argumentation to guide interpretation of legal texts

  • Application of linguistic theories of syntax, semantics, pragmatics, and discourse to legal texts

  • Adaptation of NLP tools to the particularities of legal texts

  • Implications of the above developments for law students and legal education

Contribution Evaluation

To maintain ASAIL’s relevance in the larger rapidly-moving field of legal text analytics, paper submissions must explicitly identify their substantial contribution to the state of the art and provide a satisfying amount of discussion. Possible forms of substantial contributions include:

  • Application of novel NLP techniques to a known corpus;

  • Application of known NLP techniques to a novel corpus;

  • Detailed survey and analysis of a novel corpus that will be shared with the community and/or exhibits phenomena of broader interest;

  • In-depth discussion of relevant works in argumentative position papers.

In explaining a paper’s contribution, the authors should present, as well as discuss, their data, results and model behavior in sufficient depth, and go beyond reporting common metrics. Program committee members will be instructed to review submissions according to this standard.


The ASAIL workshops strive for inclusiveness and the organizing committee encourages submissions of work concerning all legal systems, traditions, and languages.

Papers Solicited

We invite papers written in English on, and demonstrations of, original work on the above listed and other aspects of automated detection, extraction and analysis of semantic information in legal texts. Two types of papers are solicited:

  • full research papers (10 pages in the approved style plus bibliography); and

  • short position and demonstration papers (5 pages in the approved style plus bibliography).

While the bibliography is extraneous to the page limit, papers should be self-contained as ASAIL proceedings do not include appendices. A Program Committee will review both types of papers using the conference review system. Submissions will be evaluated on appropriateness for this call, originality of the research described and technical quality. Authors of selected papers will be invited to present the papers at the Workshop: 30-minute presentations (20+10 minutes of questions) for full research papers and 15-minute presentations for position and demonstration papers (10+5 minutes of questions).

Anonymous Review

ASAIL uses a double-blind peer-review process and authors are required to submit their papers without an author block on the first page. They further are responsible to avoid any identifying text in the body (e.g. citing “our work”), to the extent possible.

Format & Submission

Assuming enough submissions of sufficient quality are received, accepted papers will be published as part of the workshop proceedings at CEUR-WS, as in prior ASAIL workshops. Hence, all papers must follow the two-column CEUR-WS Layout [Latex, Word]. Papers not conforming to the style or exceeding the length limitation will be rejected without review. Papers must be submitted via the ASAIL 2021 Easychair system by the due date.

Workshop Format

Both the morning and afternoon session will likely include full and short paper presentations with subsequent Q&A. In order to maximize inclusiveness, the organizing committee will decide on other elements in the workshop schedule after all submissions have been received. Possible additions to the program include an invited speaker and moderated discussion sessions.

Important Dates

Submissions due: April 26 May 3, 2021

Authors are strongly encouraged to submit an early abstract of their submission.

Accept/Reject notification: May 26, 2021

Camera-Ready Papers due: June 4, 2021

Organizing Committee

  • Kevin D. Ashley, University of Pittsburgh

  • Katie Atkinson, University of Liverpool

  • Karl Branting, MITRE Corporation

  • Enrico Francesconi, Italian National Research Council (ITTIG-CNR), Publications Office of the EU

  • Matthias Grabmair, Technical University of Munich

  • Vern R. Walker, Maurice A. Deane School of Law at Hofstra University

  • Bernhard Waltl, BMW Group AG

  • Adam Wyner, Swansea University

Program Committee

  • Tommaso Agnoloni, Italian National Research Council (ITTIG-CNR)

  • David Restrepo Amariles, HEC Paris

  • Elliott Ash, ETH Zurich

  • Floris Bex, Utrecht University

  • Luigi Di Caro, University of Torino

  • Víctor Rodríguez Doncel, Universidad Politécnica de Madrid

  • Chris Gianella, MITRE Corporation

  • Rajaa El Hamdani, HEC Paris

  • Francesca Lagioia, European University Institute

  • Marco Lippi, University of Modena and Reggio Emilia

  • Mi-Young Kim, University of Alberta

  • Masoud Makrehchi, University of Ontario

  • Monica Palmirani, University of Bologna

  • Craig Pfeifer, MITRE Corporation

  • Georg Rehm, DFKI

  • Livio Robaldo, Swansea University

  • Jaromir Savelka, Carnegie Mellon University

  • Frank Schilder, Thomson Reuters

  • Giulia Venturi, Italian National Research Council (ILC-CNR)

  • Serena Villata, Université de Nice, Sophia Antipolis