Aarhus University Seal

Turning Bilingual Lexicography Upside Down: Improving Quality and Productivity with New Methods and Technology

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review


This is a report from the real world. It informs about the outcome of a project, which the author conducted during a months-long research stay at the Danish company Ordbogen where he integrated its R&D team. The first part of the project was to test machine translation and find out to what extent it is usable in the compilation of bilingual lexicographical databases. The hypothesis was that the technology was not yet mature. But surprisingly, it turned out that the accuracy rate is already so high that it is worth considering how to implement it. The second part of the project aimed at further developing an idea formulated by Fuertes-Olivera et al. (2018) on how to invert a dictionary without losing semantic content. The new vision is to compile a monolingual L2 database, bilingualize it to an L2-L1 database using machine translation, and then invert the relationship between L2 lemmata and L1 equivalents using the L1 definitions of the L2 lemmata as the axis. The third part of the project was to test this idea using a specially designed ad-hoc program. The program automatically uploads relevant data from existing lexicographical databases, translates L2 definitions and example sentences into L1, suggests adequate L1 equivalents, and eventually inverts the relationship between the two languages. It worked, but the methodology still needs further refinement to be implementable on a large scale. The report concludes by listing some of the remaining challenges and defining the new role of the lexicographer in this type of project.
Original languageEnglish
Pages (from-to)66-87
Number of pages22
Publication statusPublished - Mar 2022

    Research areas

  • Automatic inversion, Auxiliary language, Bilingual lexicography, Digital technology, Human versus artificial lexicographer, Interdisciplinary collaboration, Lexicographical R&D, Lexicographical database, Machine translation, Object language

See relations at Aarhus University Citationformats

ID: 227093529