Answer Set Programming for controlled natural language processing

Rolf Schwitter; Stephen C. Guy

Answer Set Programming for controlled natural language processing

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

Abstract

Answer Set Programming is a compelling non-monotonic knowledge representation paradigm for representing specifications in controlled natural language and reasoning about them. In this paper, we introduce the controlled natural language PENGASP and discuss the kind of answer set programs that the PENGASP system automatically generates for a given specification. The controlled natural language PENGASP is unique, since it is the first controlled natural language that uses Answer Set Programming as target language for reasoning, in particular for question answering. PENGASP allows us to specify factual and terminological knowledge, to combine weak and strong negation in order to specify a local form of the closed world assumption, to deal with cardinality constraints, to specify arithmetic operations, and to express defaults and exceptions. An emerging PENGASP specification can be queried in controlled natural language using closed world and open world reasoning depending on the information available in the specification.

Original language	English
Title of host publication	Joint Proceedings of the 2nd Workshop on Natural Language Processing and Automated Reasoning, and the 2nd International Workshop on Learning and Nonmonotonic Reasoning at LPNMR 2015
Editors	Marcello Balduccini, Alessandra Mileo, Ekaterina Ovchinnikova, Aless Russo, Peter Schuller
Place of Publication	NUI Galway, Ireland
Publisher	INSIGHT Centre for Data Analytics
Pages	15-26
Number of pages	12
Publication status	Published - 2015
Event	Workshop on Natural Language Processing and Automated Reasoning (2nd : 2015), and International Workshop on Learning and Nonmonotonic Reasoning (2nd : 2015) - Lexington, KY Duration: 27 Sept 2015 → 27 Sept 2015

Workshop

Workshop	Workshop on Natural Language Processing and Automated Reasoning (2nd : 2015), and International Workshop on Learning and Nonmonotonic Reasoning (2nd : 2015)
City	Lexington, KY
Period	27/09/15 → 27/09/15

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http://www.peterschueller.com/pub/2015/nlpar2015-proceedings.pdf

Cite this

Schwitter, R., & Guy, S. C. (2015). Answer Set Programming for controlled natural language processing. In M. Balduccini, A. Mileo, E. Ovchinnikova, A. Russo, & P. Schuller (Eds.), Joint Proceedings of the 2nd Workshop on Natural Language Processing and Automated Reasoning, and the 2nd International Workshop on Learning and Nonmonotonic Reasoning at LPNMR 2015 (pp. 15-26). INSIGHT Centre for Data Analytics. http://www.peterschueller.com/pub/2015/nlpar2015-proceedings.pdf

Schwitter, Rolf ; Guy, Stephen C. / Answer Set Programming for controlled natural language processing. Joint Proceedings of the 2nd Workshop on Natural Language Processing and Automated Reasoning, and the 2nd International Workshop on Learning and Nonmonotonic Reasoning at LPNMR 2015. editor / Marcello Balduccini ; Alessandra Mileo ; Ekaterina Ovchinnikova ; Aless Russo ; Peter Schuller. NUI Galway, Ireland : INSIGHT Centre for Data Analytics, 2015. pp. 15-26

@inproceedings{507bd3a9081c477db03d7f34d54dc227,

title = "Answer Set Programming for controlled natural language processing",

abstract = "Answer Set Programming is a compelling non-monotonic knowledge representation paradigm for representing specifications in controlled natural language and reasoning about them. In this paper, we introduce the controlled natural language PENGASP and discuss the kind of answer set programs that the PENGASP system automatically generates for a given specification. The controlled natural language PENGASP is unique, since it is the first controlled natural language that uses Answer Set Programming as target language for reasoning, in particular for question answering. PENGASP allows us to specify factual and terminological knowledge, to combine weak and strong negation in order to specify a local form of the closed world assumption, to deal with cardinality constraints, to specify arithmetic operations, and to express defaults and exceptions. An emerging PENGASP specification can be queried in controlled natural language using closed world and open world reasoning depending on the information available in the specification.",

author = "Rolf Schwitter and Guy, {Stephen C.}",

year = "2015",

language = "English",

pages = "15--26",

editor = "Marcello Balduccini and Alessandra Mileo and Ekaterina Ovchinnikova and Aless Russo and Peter Schuller",

booktitle = "Joint Proceedings of the 2nd Workshop on Natural Language Processing and Automated Reasoning, and the 2nd International Workshop on Learning and Nonmonotonic Reasoning at LPNMR 2015",

publisher = "INSIGHT Centre for Data Analytics",

note = "Workshop on Natural Language Processing and Automated Reasoning (2nd : 2015), and International Workshop on Learning and Nonmonotonic Reasoning (2nd : 2015) ; Conference date: 27-09-2015 Through 27-09-2015",

}

Schwitter, R & Guy, SC 2015, Answer Set Programming for controlled natural language processing. in M Balduccini, A Mileo, E Ovchinnikova, A Russo & P Schuller (eds), Joint Proceedings of the 2nd Workshop on Natural Language Processing and Automated Reasoning, and the 2nd International Workshop on Learning and Nonmonotonic Reasoning at LPNMR 2015. INSIGHT Centre for Data Analytics, NUI Galway, Ireland, pp. 15-26, Workshop on Natural Language Processing and Automated Reasoning (2nd : 2015), and International Workshop on Learning and Nonmonotonic Reasoning (2nd : 2015), Lexington, KY, 27/09/15. <http://www.peterschueller.com/pub/2015/nlpar2015-proceedings.pdf>

Answer Set Programming for controlled natural language processing. / Schwitter, Rolf; Guy, Stephen C.
Joint Proceedings of the 2nd Workshop on Natural Language Processing and Automated Reasoning, and the 2nd International Workshop on Learning and Nonmonotonic Reasoning at LPNMR 2015. ed. / Marcello Balduccini; Alessandra Mileo; Ekaterina Ovchinnikova; Aless Russo; Peter Schuller. NUI Galway, Ireland: INSIGHT Centre for Data Analytics, 2015. p. 15-26.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Answer Set Programming for controlled natural language processing

AU - Schwitter, Rolf

AU - Guy, Stephen C.

PY - 2015

Y1 - 2015

N2 - Answer Set Programming is a compelling non-monotonic knowledge representation paradigm for representing specifications in controlled natural language and reasoning about them. In this paper, we introduce the controlled natural language PENGASP and discuss the kind of answer set programs that the PENGASP system automatically generates for a given specification. The controlled natural language PENGASP is unique, since it is the first controlled natural language that uses Answer Set Programming as target language for reasoning, in particular for question answering. PENGASP allows us to specify factual and terminological knowledge, to combine weak and strong negation in order to specify a local form of the closed world assumption, to deal with cardinality constraints, to specify arithmetic operations, and to express defaults and exceptions. An emerging PENGASP specification can be queried in controlled natural language using closed world and open world reasoning depending on the information available in the specification.

AB - Answer Set Programming is a compelling non-monotonic knowledge representation paradigm for representing specifications in controlled natural language and reasoning about them. In this paper, we introduce the controlled natural language PENGASP and discuss the kind of answer set programs that the PENGASP system automatically generates for a given specification. The controlled natural language PENGASP is unique, since it is the first controlled natural language that uses Answer Set Programming as target language for reasoning, in particular for question answering. PENGASP allows us to specify factual and terminological knowledge, to combine weak and strong negation in order to specify a local form of the closed world assumption, to deal with cardinality constraints, to specify arithmetic operations, and to express defaults and exceptions. An emerging PENGASP specification can be queried in controlled natural language using closed world and open world reasoning depending on the information available in the specification.

M3 - Conference proceeding contribution

SP - 15

EP - 26

BT - Joint Proceedings of the 2nd Workshop on Natural Language Processing and Automated Reasoning, and the 2nd International Workshop on Learning and Nonmonotonic Reasoning at LPNMR 2015

A2 - Balduccini, Marcello

A2 - Mileo, Alessandra

A2 - Ovchinnikova, Ekaterina

A2 - Russo, Aless

A2 - Schuller, Peter

PB - INSIGHT Centre for Data Analytics

CY - NUI Galway, Ireland

T2 - Workshop on Natural Language Processing and Automated Reasoning (2nd : 2015), and International Workshop on Learning and Nonmonotonic Reasoning (2nd : 2015)

Y2 - 27 September 2015 through 27 September 2015

ER -

Schwitter R, Guy SC. Answer Set Programming for controlled natural language processing. In Balduccini M, Mileo A, Ovchinnikova E, Russo A, Schuller P, editors, Joint Proceedings of the 2nd Workshop on Natural Language Processing and Automated Reasoning, and the 2nd International Workshop on Learning and Nonmonotonic Reasoning at LPNMR 2015. NUI Galway, Ireland: INSIGHT Centre for Data Analytics. 2015. p. 15-26

Answer Set Programming for controlled natural language processing

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