The jobs puzzle: Taking on the challenge via controlled natural language processing

Research output: Contribution to journalConference paperResearchpeer-review

Abstract

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.

LanguageEnglish
Pages487-501
Number of pages15
JournalTheory and Practice of Logic Programming
Volume13
Issue number4-5
DOIs
Publication statusPublished - Jul 2013
Event29th International Conference on Logic Programming - Istanbul, Turkey, Istanbul
Duration: 24 Jul 201329 Jul 2013

Fingerprint

Answer Sets
Formal languages
Specification languages
Natural Language
Specifications
Formal Languages
Specification Languages
Processing
Notation
Encoding
Specification

Cite this

@article{f801a28e341345dba6165ceb5694da5b,
title = "The jobs puzzle: Taking on the challenge via controlled natural language processing",
abstract = "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.",
author = "Rolf Schwitter",
year = "2013",
month = "7",
doi = "10.1017/S1471068413000306",
language = "English",
volume = "13",
pages = "487--501",
journal = "Theory and Practice of Logic Programming",
issn = "1471-0684",
publisher = "Cambridge University Press",
number = "4-5",

}

The jobs puzzle : Taking on the challenge via controlled natural language processing. / Schwitter, Rolf.

In: Theory and Practice of Logic Programming, Vol. 13, No. 4-5, 07.2013, p. 487-501.

Research output: Contribution to journalConference paperResearchpeer-review

TY - JOUR

T1 - The jobs puzzle

T2 - Theory and Practice of Logic Programming

AU - Schwitter, Rolf

PY - 2013/7

Y1 - 2013/7

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84884764040&partnerID=8YFLogxK

U2 - 10.1017/S1471068413000306

DO - 10.1017/S1471068413000306

M3 - Conference paper

VL - 13

SP - 487

EP - 501

JO - Theory and Practice of Logic Programming

JF - Theory and Practice of Logic Programming

SN - 1471-0684

IS - 4-5

ER -