Paraconsistency and Word Puzzles
| Autor: | Paul Fodor, Tiantian Gao, Michael Kifer |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Logic in Computer Science Computer science Semantics (computer science) Computer Science - Artificial Intelligence Context (language use) 02 engineering and technology computer.software_genre 01 natural sciences Theoretical Computer Science Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Attempto Controlled English 0101 mathematics business.industry 010102 general mathematics Paraconsistent logic language.human_language Logic in Computer Science (cs.LO) First-order logic Artificial Intelligence (cs.AI) Controlled natural language Computational Theory and Mathematics Hardware and Architecture language 020201 artificial intelligence & image processing Artificial intelligence business computer Software Natural language processing Natural language Stable model semantics |
| Popis: | Word puzzles and the problem of their representations in logic languages have received considerable attention in the last decade (Ponnuruet al. 2004; Shapiro 2011; Baral and Dzifcak 2012; Schwitter 2013). Of special interest is the problem of generating such representations directly from natural language (NL) or controlled natural language (CNL). An interesting variation of this problem, and to the best of our knowledge, scarcely explored variation in this context, is when the input information is inconsistent. In such situations, the existing encodings of word puzzles produce inconsistent representations and break down. In this paper, we bring the well-known type of paraconsistent logics, calledAnnotated Predicate Calculus(APC) (Kifer and Lozinskii 1992), to bear on the problem. We introduce a new kind of non-monotonic semantics for APC, calledconsistency preferred stable modelsand argue that it makes APC into a suitable platform for dealing with inconsistency in word puzzles and, more generally, in NL sentences. We also devise a number of general principles to help the user choose among the different representations of NL sentences, which might seem equivalent but, in fact, behave differently when inconsistent information is taken into account. These principles can be incorporated into existing CNL translators, such as Attempto Controlled English (ACE) (Fuchset al. 2008) and PENG Light (White and Schwitter 2009). Finally, we show that APC with the consistency preferred stable model semantics can be equivalently embedded in ASP with preferences over stable models, and we use this embedding to implement this version of APC in Clingo (Gebseret al. 2011) and its Asprin add-on (Brewkaet al. 2015). |
| Databáze: | OpenAIRE |
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