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GaiusT 2.0: Evolution of a Framework for Annotating Legal Documents

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Metadata and Semantics Research (MTSR 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 672))

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Abstract

Semantic annotation technologies support the extraction of legal concepts, for example rights and obligations, from legal documents. For software engineers, the final goal is to identify compliance requirements a software system has to fulfill in order to comply with a law or regulation. That implies analyzing and annotating legal documents in prescriptive natural language, still an open problem for research in the field. In this paper we describe GaiusT 2.0, a system for extracting requirements from legal documents. GaiusT 2.0 is the result of the evolution of GaiusT, and has been designed and implemented as a web-based system intended to semi-automate the extraction process. Results of the application of GaiusT 2.0 show that the new version improves performance of the extraction process and also makes the tool more usable.

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Notes

  1. 1.

    • Recall is a measure of how well the tool performs in finding relevant items TP/(TP + FN);

    • Precision is a measure of how well the tool performs in not returning irrelevant items TP/(TP + FP);

    • Fallout is a measure of how quickly precision drops as recall is increased FP/(FP + TN);

    • Accuracy is a measure of how well the tool identifies relevant items and rejects irrelevant ones (TP + TN)/N;

    • Error is a measure of how much the tool is prone to accept irrelevant items and rejects relevant ones (FP + FN)/N;

    • F-measure is a harmonic mean of recall and precision 2 × Recall × Precision/(Recall + Precision)

    where TP is the number of items correctly assigned to the category; FP is the number of items incorrectly assigned to the category; FN is the number of items incorrectly rejected from the category; TN is the number of items correctly rejected from the category; and N is the total number of items N = TP + FP + FN + TN.

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Acknowledgements

Nicola Zeni’s work was supported in part by the ERC advanced grant 267856 ‘Lucretius: Foundations for Software Evolution’. Our thanks go to the experts and users who made themselves available to test GaiusT 2.0.

Author information

Authors and Affiliations

  1. Department of Information Engineering and Computer Science, University of Trento, Trento, Italy

    Nicola Zeni

  2. Department of Industrial Engineering, University of Trento, Trento, Italy

    Luisa Mich

  3. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, CA, Canada

    John Mylopoulos

Authors
  1. Nicola Zeni
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  2. Luisa Mich
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  3. John Mylopoulos
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Corresponding author

Correspondence to Luisa Mich .

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Editors and Affiliations

  1. Alexander Technological Educational Institute of Thessaloniki, Thessaloniki, Greece

    Emmanouel Garoufallou

  2. Alexander Technological Educational Inst , Rome, Italy

    Imma Subirats Coll

  3. Sapienza University of Rome , Rome, Italy

    Armando Stellato

  4. Drexel University, Philadelphia, Pennsylvania, USA

    Jane Greenberg

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Zeni, N., Mich, L., Mylopoulos, J. (2016). GaiusT 2.0: Evolution of a Framework for Annotating Legal Documents. In: Garoufallou, E., Subirats Coll, I., Stellato, A., Greenberg, J. (eds) Metadata and Semantics Research. MTSR 2016. Communications in Computer and Information Science, vol 672. Springer, Cham. https://doi.org/10.1007/978-3-319-49157-8_4

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  • DOI: https://doi.org/10.1007/978-3-319-49157-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49156-1

  • Online ISBN: 978-3-319-49157-8

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