, Volume 4, Issue 1, pp 3–21 | Cite as

Maintaining the balance between knowledge and the lexicon in terminology: a methodology based on frame semantics

  • Marie-Claude L’Homme
Original Paper


This paper argues for an approach to terms—based on Frame Semantics (Fillmore in Ann N Y Acad Sci Conf Origin Dev Lang Speech 280:20–32, 1976; Fillmore and Baker in A Frames Approach to Semantic Analysis, 313–339, 2010)—that takes into account their linguistic properties and shows how terms and their properties are connected formally to the expression of knowledge in specialized fields. I briefly present the theoretical assumptions underlying this proposal. The main part of the article describes the methodology devised to implement the proposal in two terminological resources that are under development at the Observatoire de linguistique Sens-Texte (OLST). The methodology that comprises seven main steps is based on that of FrameNet (, 2017. Accessed 20 January 2017) (Ruppenhofer et al. in FrameNet II: extended theory and practice., 2016. Accessed 27 January 2017), the lexical implementation of Frame Semantics. I illustrate the methodology by applying it to terms that belong to the field of endangered species, a subfield of the environment.


Terms Predicative units Frames Frame semantics Terminological resource Environment 



This research is supported by the Social Sciences and Humanities Research Council (SSHRC) of Canada and by the Fonds de recherche du Québec—Société et culture (FRQ-SC). I would like to thank the members of my research team who contributed in one way or another to the Framed DiCoEnviro project. I also extend my thanks to two anonymous reviewers whose comments helped clarify many parts of the paper.


  1. Azoulay, D. 2017. Frame-based knowledge representation using large specialized corpora. In: Proceedings of the AAAI spring symposium on computational construction grammar and natural language understanding, Stanford University, CA.Google Scholar
  2. Bernier-Colborne, Gabriel. 2016. Aide à l’identification de relations lexicales au moyen de la sémantique distributionnelle et son application à un corpus bilingue du domaine de l’environnement. Ph.D Thesis presented at the Université de Montréal, Montréal.Google Scholar
  3. DiCoEnviro. 2017. Dictionnaire fondamental de l’environnement. Accessed 31 July 2017.
  4. Drouin, P. 2003. Term extraction using non-technical corpora as a point of leverage. Terminology 9 (1): 99–117.CrossRefGoogle Scholar
  5. EcoRessources. Terminological resources for the environment. 2017. Accessed 31 July 2017.
  6. Faber, P., P. León-Araúz, and A. Reimerink. 2016. EcoLexicon: New features and challenges. In GLOBALEX 2016: lexicographic resources for human language technology and 10th edition of the language resources and evaluation conference, ed. by Kernerman, I., I. Kosem Trojina, S. Krek, and L. Trap-Jensen, 73-80. Portorož.Google Scholar
  7. Fillmore, C.J. 1976. Frame semantics and the nature of language. In Annals New York Academy of Sciences: Conference on the Origin and Development of Language and Speech 280: 20–32.CrossRefGoogle Scholar
  8. Fillmore, C.J. 1985. Frames and the semantics of understanding. Quaderni di Semantica 6: 222–254.Google Scholar
  9. Fillmore, C. J., and B.T. Atkins. 1992. Toward a frame-based Lexicon: the semantics of RISK and its neighbors.” In Frames, Fields and Contrasts, ed. by A. Lehrer, and E. Feder Kittay, 75–102. Hillsdale, New Jersey: Lawrence Erlbaum Assoc.Google Scholar
  10. Fillmore, C.J., and C. Baker. 2010. A frames approach to semantic analysis. In Handbook of Linguistic Analysis, ed. B. Heine, and H. Narrog, 313–339. Oxford: Oxford University Press.Google Scholar
  11. Fillmore, C., M.R.L. Petruck, J. Roppenhofer, and A. Wright. 2003. FrameNet in action: the case of attaching. International Journal of Lexicography 16 (2): 297–332.CrossRefGoogle Scholar
  12. Forest, D., H. Brousseau, P. Drouin, and G. Bernier-Colborne. 2015. L’environnement vu par ses documents: utilisation de techniques de fouille de textes dans un contexte de description linguistique. In 13e Journées internationales d’analyse statistique des données textuelles, Nice, France.Google Scholar
  13. Framed DiCoEnviro. 2017. A Framed Version of DiCoEnviro. Accessed 31 July 2017.
  14. FrameNet. 2017. Accessed 20 January 2017.
  15. Ghazzawi, N. 2016. Du terme prédicatif au cadre sémantique: méthodologie de compilation d’une ressource terminologique pour les termes arabes de l’informatique. Ph.D. Thesis, presented at the Université de Montréal, Montreal.Google Scholar
  16. Hadouche, F., S. Desgroseillers, J. Pimentel, M.C. L’Homme, and G. Lapalme. 2011. Identification des participants de lexies prédicatives: évaluation en performance et en temps d’un système d’annotation automatique. In Terminologie et intelligence artificielle (TIA 2011), Institut national des langues orientales INALCO, Paris.Google Scholar
  17. L’Homme, M.C. 2015. Découverte de cadres sémantiques dans le domaine de l’environnement: le cas de l’influence objective. Terminàlia 12: 29–40.Google Scholar
  18. L’Homme, M.C. 2016. Terminologie de l’environnement et sémantique des cadres. In Congrès mondial de linguistique française (CMLF 2016), Tours, France.Google Scholar
  19. L’Homme, M.C., C. Subirats, and B. Robichaud. 2016. A Proposal for combining “general” and specialized frames. In Proceedings of the workshop on cognitive aspects of the Lexicon. 156–165, Osaka, Japan.Google Scholar
  20. Pimentel, J. 2013. Methodological bases for assigning terminological equivalents. A Contribution. Terminology 19 (2): 237–257.CrossRefGoogle Scholar
  21. Ruppenhofer, J, M. Ellsworth, M. Petruck, C. Johnson, and C. Baker, and J. Scheffczyk. 2016. FrameNet II: extended theory and practice. Accessed 27 January 2017.
  22. Schmid, H. 1994. Probabilistic part-of-speech tagging using decision trees. In Proceedings of international conference on new methods in language processing, Manchester, UK.Google Scholar
  23. Schmidt, T. 2009. The Kicktionary—a multilingual lexical resources of football language. In Multilingual FrameNets in Computational Lexicography. Methods and Applications, ed. Boas, H.C., 101–134. Berlin/New York: Mouton de Gruyter.Google Scholar
  24. Wildlife Ontology (2017). Accessed 20 January 2017.

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Observatoire de linguistique Sens-Texte (OLST)Université de MontréalMontréalCanada

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