Skip to main content
SpringerLink
Log in

Resolving Deontic Operator Conflicts in Legal Documents

  • Conference paper
Applications and Innovations in Intelligent Systems VIII

  • 65 Accesses

Abstract

This paper presents experimental work on the development of a system that is aimed at (semi)-automatically identifying deontic inconsistencies in legal documents. The target text with which the system was tried was the British data protection Act (1984).

The motivation behind our project was to assist authors of such documents to identify and hopefully resolve inconsistencies and ambiguities before the document in question is released to the target audience.

The main difficulty in writing legal documents does not lie in the structural complexities of the language, but rather in the meaning of the phrases used. A particular problem arises in the form of deontic operators, which may mislead the unwary reader especially if he/she is not familiar with the legal domain.

Our system attempts to solve potential problems of this kind, using both the syntactic and semantic information contained within a natural language legal text. The system employs the Conceptual Graph knowledge representation formalism in conjunction with a modified parser to create structures, which can subsequently be compared at the semantic level, regardless of differences in the surface syntax.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abo, A.V. and Ullman, J.D. (1972) The theory of Parsing, Translation and Compiling, Vol: Parsing, Prentice-Hall, Englewood Cliffs, N.J.

    Google Scholar 

  2. Berg-Cross, G. and Price, M. E. (1989) Acquiring and managing knowledge using a conceptual structures approach, IEEE Transactions on Systems, Man and Cybernetics, vol. 19:3, p.513–27.

    Article  Google Scholar 

  3. Calder, J., Klein, E., and Zeevat, H. (1988) Unification Categorial Grammar: A Concise Extendable Grammar for Natural Language Processing, COUNG-88, 83–86.

    Google Scholar 

  4. Clocksin, W. and Mellish, C. (1981) Programming in PROLOG, Springer-Verlag: Berlin.

    MATH  Google Scholar 

  5. Dowty, D. R., Wall, R. E., and Peters, S., Introduction to Montague Semantics, Reidel, Dortrecht, 1981

    Google Scholar 

  6. Early, J. (1970) An Efficient Context Free Parsing Algorithm, Communications of the A.C.M., v.14, 453–460.

    Google Scholar 

  7. Ellis, G. (1993) Efficient Retrieval from Hierarchies of Objects using Lattice Operations, in G. Mineau, B. Moulin, I.F. Sowa, eds, Conceptual Graphs for Knowledge Representation: First International Conference on Conceptual Structures, ICCS’93, Quebec City, Canada, August 4-7, 1993 Proceedings, Springer-Verlag: Berlin Heidelberg.

    Google Scholar 

  8. Fargues. J., Landau, M-C., Degaud, A. and Catach, L. (1986) Conceptual Graphs for semantics and knowldge processing, IBM Journal of Research and Development. v.30:1, January 1986, p.70–79.

    Article  Google Scholar 

  9. Fillmore, C. J., “The Case for Case” In Universals in Linguistic Theory. Edited by E. Bach and R. T. Harms. Holt, Reinhart and Willson, New York, 1968.

    Google Scholar 

  10. Knuth, D.E. (1965) On the translation of languages from left to right, Information and Control, v.8, 607–639.

    Article  MathSciNet  Google Scholar 

  11. Konstantinou, V., Sykes, J. and Yannopolous, G. (1992) Legal Reasoning Methodology: The missing link, Law, Computers and Artificial Intelligence, Vol.3:1, p29–46.

    Google Scholar 

  12. Landau, M-C. (1990) Semantic representation of texts, COUNG-90 Proceedings, Vol 2, p239–244.

    Google Scholar 

  13. Levinson, R. and Ellis, G. (1992) Multilevel hierarchical retrieval, KnowledgeBased Systems, v.5:3,233–244.

    Article  Google Scholar 

  14. Minski, M., “A Framework for Representing Knowledge.” In Mind Design. Edited by J. Haugeland. Cambridge, MA: The MIT Press, 1981, 95–128.

    Google Scholar 

  15. Nogier, J-F. and Zock, M. (1992) Lexical Choice as Pattern Matching, Knowledge-Based Systems, v.5:3, 200–212.

    Article  Google Scholar 

  16. Pau, L. F. and Nielsen, S.S. (1989) Conceptual Graphs as a visual language for knowledge acquisition in architectural expert systems, SIGART Newsletter, Special Isssue on Knowledge Acquisition, no. 108, April 1989, p.151.

    Google Scholar 

  17. Pareira, F.C.N. and Warren, D.H.D. (1980) Definite Clause Grammars for language analysis-a survey of the formalism and a comparison with augmented transition networks, Artificial Intelligence, v.13, 231–278.

    Article  MathSciNet  Google Scholar 

  18. Pollard. C. and Sag, I.A. (1987) Information Based Syntax and Semantics, CLSI Lecture Notes 13, Stanford: CLSI

    Google Scholar 

  19. Quillian, M. R. (1968) “Semantic Memory”, In Semantic Information Processing. Edited by M. Minsky. Cambridge. MA: The MIT Press, 227–270.

    Google Scholar 

  20. Shank. R. C., Conceptual Information Processing. North Holland, Amsterdam, 1975.

    Google Scholar 

  21. Shank, R. C., and Ableson, R. Scripts, Plans, Goals and Understanding. Hillsdale, NJ: Lawrence Erlbaum Associates, 1997.

    Google Scholar 

  22. Sheiber, S.M. (1988) An Introduction to Unification Based Approaches to Grammar, CSLI Licture Notes 4, Stanford:CLSI.

    Google Scholar 

  23. Slagle, J. R., Gardiner, D. A. and Han, K. (1990) Knowledge specification of an expert system, IEEE Expert: hp2.p:4:ehp2., 20–38

    Google Scholar 

  24. Sowa, J. F. (1981) A conceptual schema for knowledge based systems, Proceedings of the Workshop on data Abstractino, Databases, and Conceptual Modelling, ACM, p193–195.

    Google Scholar 

  25. Sowa, J. F. 1984. Conceptual Structures: Information Processing in Mind and Machine, Addison-Wesley, Reading, MA.

    Google Scholar 

  26. Sowa, J.F. and Way, E.C. (1986) Implementing a Semantic Interpreter Using Conceptual Graphs, IBM Journal of Research and Development, v.30:15,57–69.

    Article  Google Scholar 

  27. Sowa, J. F. 1994 Knowledge Representation: Logical, Philosophical, and Computational Foundations, Preliminary Edition, ICCS94.

    Google Scholar 

  28. Sowa, J. F. (2000) Knowledge Representation: Logical, Philosophical and Computational foundations, Brooks/Cole.

    Google Scholar 

  29. Sykes, J. T., Konstantinou, V. and Morse, P. L. R, “An incremental parser for Concepmal Graphs”, Proceedings of the 3rd International Conference on Conceptual Structures, University of California, Santa Cruz, August 1995.

    Google Scholar 

  30. Velardi, P., Pazienza, M.T., and DeGiovanetti, M. (1988) Conceptual Graphs for the Analysis and Generation of Sentences, IBM Journal of Research and Development, v.32:2, 251–267.

    Article  Google Scholar 

  31. Way, E.C. (1992) Metaphor as a mechanism for reorganizing the type hierarchy, Knowledge-Based Systems, v.5:3, 223–232.

    Article  Google Scholar 

  32. Zeevat, H., Klein, E., and Calder, J. (1987) An Introduction to Unification Categorial Grammar. in Edinburgh Working Papers in Cognitive Science, Vol. 1: Categorial Grammar, Unification Grammar and Parsing, ed. by N.J. Haddock, E. Klein and G. Morril.

    Google Scholar 

  33. Zeevat, H. (1998) Combining Categorial Grammar and Unification in Natural Language Parsing and Linguistic Theories, ed by Reyle, U. and Roher, C., D. Reidel, 202–229.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Harrow School of Computer Science, University of Westminster, Northwick Park, Watford Road, Harrow, Middlesex, HA1 3TP, England

    J. T. Sykes & V. Konstantinou

Authors
  1. J. T. Sykes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. Konstantinou
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. International Teledemocracy Centre, Napier University, Edinburgh, UK

    Ann Macintosh BSc, CEng

  2. Department of Accounting and Management Science, Portsmouth Business School, University of Portsmouth, Portsmouth, UK

    Mike Moulton BSc

  3. Department of Computer Science, University of Liverpool, Liverpool, UK

    Frans Coenen PhD

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag London

About this paper

Cite this paper

Sykes, J.T., Konstantinou, V. (2001). Resolving Deontic Operator Conflicts in Legal Documents. In: Macintosh, A., Moulton, M., Coenen, F. (eds) Applications and Innovations in Intelligent Systems VIII. Springer, London. https://doi.org/10.1007/978-1-4471-0275-5_8

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-0275-5_8

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-402-4

  • Online ISBN: 978-1-4471-0275-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation