Schaefer JF, Amann K, Kohlhase M (2020)
Publication Type: Conference contribution
Publication year: 2020
Publisher: Springer
Book Volume: 12097 LNCS
Pages Range: 406-415
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Braunschweig, DEU
ISBN: 9783030521998
DOI: 10.1007/978-3-030-52200-1_40
The Grammatical Logical Framework (GLF) is a framework for prototyping the translation of natural language sentences into logic. The motivation behind GLF was to apply it to mathematical language, as the classical compositional approach to semantics construction seemed most suitable for a domain where high precision was mandatory—even at the price of limited coverage. In particular, software for formal mathematics (such as proof checkers) require formal input languages. These are typically difficult to understand and learn, raising the entry barrier for potential users. A solution is to design input languages that closely resemble natural language. Early results indicate that GLF can be a useful tool for quickly prototyping such languages. In this paper, we will explore how GLF can be used to prototype such languages and present a new Jupyter kernel that4 adds visual support for the development of GLF-based syntax/semantics interfaces.
APA:
Schaefer, J.F., Amann, K., & Kohlhase, M. (2020). Prototyping Controlled Mathematical Languages in Jupyter Notebooks. In Anna Maria Bigatti, Jacques Carette, James H. Davenport, Michael Joswig, Timo de Wolff (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 406-415). Braunschweig, DEU: Springer.
MLA:
Schaefer, Jan Frederik, Kai Amann, and Michael Kohlhase. "Prototyping Controlled Mathematical Languages in Jupyter Notebooks." Proceedings of the 7th International Congress on Mathematical Software, ICMS 2020, Braunschweig, DEU Ed. Anna Maria Bigatti, Jacques Carette, James H. Davenport, Michael Joswig, Timo de Wolff, Springer, 2020. 406-415.
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