The jobs puzzle: Taking on the challenge via controlled natural language processing
In this paper we take on Stuart C. Shapiro's challenge of solving the Jobs Puzzle automatically and do this via controlled natural language processing. Instead of encoding the puzzle in a formal language that might be difficult to use and understand, we employ a controlled natural language as a...
Saved in:
Published in | Theory and practice of logic programming Vol. 13; no. 4-5; pp. 487 - 501 |
---|---|
Main Author | |
Format | Journal Article |
Language | English |
Published |
Cambridge, UK
Cambridge University Press
01.07.2013
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | In this paper we take on Stuart C. Shapiro's challenge of solving the Jobs Puzzle automatically and do this via controlled natural language processing. Instead of encoding the puzzle in a formal language that might be difficult to use and understand, we employ a controlled natural language as a high-level specification language that adheres closely to the original notation of the puzzle and allows us to reconstruct the puzzle in a machine-processable way and add missing and implicit information to the problem description. We show how the resulting specification can be translated into an answer set program and be processed by a state-of-the-art answer set solver to find the solutions to the puzzle. |
---|---|
Bibliography: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23 |
ISSN: | 1471-0684 1475-3081 |
DOI: | 10.1017/S1471068413000306 |