scholarly journals Model-Finding for Externally Verifying FOL Ontologies: A Study of Spatial Ontologies

2020 ◽  
Author(s):  
Shirly Stephen ◽  
Torsten Hahmann
Keyword(s):  
Systematic Study ◽  
State Of The Art ◽  
Order Logic ◽  
First Order Logic ◽  
Problem Size ◽  
Effective Measure ◽  
First Order ◽  
Highly Effective ◽  
Model Finding ◽  
Synthetic Datasets

Use and reuse of an ontology requires prior ontology verification which encompasses, at least, proving that the ontology is internally consistent and consistent with representative datasets. First-order logic (FOL) model finders are among the only available tools to aid us in this undertaking, but proving consistency of FOL ontologies is theoretically intractable while also rarely succeeding in practice, with FOL model finders scaling even worse than FOL theorem provers. This issue is further exacerbated when verifying FOL ontologies against datasets, which requires constructing models with larger domain sizes. This paper presents a first systematic study of the general feasibility of SAT-based model finding with FOL ontologies. We use select spatial ontologies and carefully controlled synthetic datasets to identify key measures that determine the size and difficulty of the resulting SAT problems. We experimentally show that these measures are closely correlated with the runtimes of Vampire and Paradox, two state-of-the-art model finders. We propose a definition elimination technique and demonstrate that it can be a highly effective measure for reducing the problem size and improving the runtime and scalability of model finding.

scholarly journals Towards closed world reasoning in dynamic open worlds

2010 ◽  
Vol 10 (4-6) ◽  
pp. 547-563 ◽  
Author(s):  
MARTIN SLOTA ◽  
JOÃO LEITE
Keyword(s):  
Semantic Web ◽  
State Of The Art ◽  
Knowledge Bases ◽  
Order Logic ◽  
First Order Logic ◽  
Static Case ◽  
First Order ◽  
Closed World ◽  
Hybrid Knowledge ◽  
First Time

AbstractThe need for integration of ontologies with nonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantics forhybrid knowledge basescomposed of both an ontology (expressed in a fragment of first-order logic) and nonmonotonic rules. These semantics have matured over the years, but only provide solutions for the static case when knowledge does not need to evolve.In this paper we take a first step towards addressing the dynamics of hybrid knowledge bases. We focus on knowledge updates and, considering the state of the art of belief update, ontology update and rule update, we show that current solutions are only partial and difficult to combine. Then we extend the existing work on ABox updates with rules, provide a semantics for such evolving hybrid knowledge bases and study its basic properties.To the best of our knowledge, this is the first time that an update operator is proposed for hybrid knowledge bases.

Principles and practice in verifying rule-based systems

1992 ◽  
Vol 7 (2) ◽  
pp. 115-141 ◽  
Author(s):  
Alun D. Preece ◽  
Rajjan Shinghal ◽  
Aïda Batarekh
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
State Of The Art ◽  
Knowledge Bases ◽  
Order Logic ◽  
First Order Logic ◽  
Rule Based ◽  
First Order ◽  
Rule Bases ◽  
System Knowledge

AbstractThis paper surveys the verification of expert system knowledge bases by detecting anomalies. Such anomalies are highly indicative of errors in the knowledge base. The paper is in two parts. The first part describes four types of anomaly: redundancy, ambivalence, circularity, and deficiency. We consider rule bases which are based on first-order logic, and explain the anomalies in terms of the syntax and semantics of logic. The second part presents a review of five programs which have been built to detect various subsets of the anomalies. The four anomalies provide a framework for comparing the capabilities of the five tools, and we highlight the strengths and weaknesses of each approach. This paper therefore provides not only a set of underlying principles for performing knowledge base verification through anomaly detection, but also a survey of the state-of-the-art in building practical tools for carrying out such verification. The reader of this paper is expected to be familiar with first-order logic.

scholarly journals Razor: Provenance and Exploration in Model-Finding

10.29007/tcvw ◽  
2018 ◽  
Author(s):  
Salman Saghafi ◽  
Daniel Dougherty
Keyword(s):  
Software Design ◽  
Security Protocols ◽  
Order Logic ◽  
First Order Logic ◽  
Mathematical Tool ◽  
Geometric Form ◽  
Provenance Information ◽  
First Order ◽  
Model Finding ◽  
Core Functionality

Razor is a model-finder for first-order theories presentedgeometric form; geometric logic is a variant of first-order logicthat focuses on ``observable'' properties. An important guidingprinciple of Razor is that it be accessible to users who arenot necessarily expert in formal methods; application areasinclude software design, analysis of security protocols andpolicies, and configuration management.A core functionality of the tool is that it supportsexploration of the space of models of a given input theory,as well as presentation of provenance information about theelements and facts of a model. The crucial mathematical tool isthe ordering relation on models determined by homomorphism, andRazor prefers models that are minimal with respect to thishomomorphism-ordering.

scholarly journals Satisfiability Checking and Query Answering for Large Ontologies

10.29007/n1sv ◽  
2018 ◽  
Author(s):  
Christoph Weidenbach ◽  
Patrick Wischnewski
Keyword(s):  
State Of The Art ◽  
The State ◽  
Order Logic ◽  
Query Answering ◽  
First Order Logic ◽  
First Order ◽  
Satisfiability Checking ◽  
Superposition Calculus

In this paper we develop a sound, complete and terminating superposition calculusplus a query answering calculus for the BSH-Y2 fragment of theBernays-Schoenfinkel Horn class of first-order logic.BSH-Y2 can be used to represent expressive ontologies.In addition to checking consistency, our calculus supports query answeringfor queries with arbitrary quantifier alternations.Experiments on BSH-Y2 (fragments) of several large ontologies show that ourapproach advances the state of the art.

scholarly journals Inputs, Outputs, and Composition in the Logic of Information Flows

2020 ◽  
Author(s):  
Heba Aamer ◽  
Bart Bogaerts ◽  
Dimitri Surinx ◽  
Eugenia Ternovska ◽  
Jan Van den Bussche
Keyword(s):  
Systematic Study ◽  
General Framework ◽  
Expressive Power ◽  
Order Logic ◽  
First Order Logic ◽  
Information Flows ◽  
First Order ◽  
Sequential Composition ◽  
Inputs And Outputs

The logic of information flows (LIF) is a general framework in which tasks of a procedural nature can be modeled in a declarative, logic-based fashion. The first contribution of this paper is to propose semantic and syntactic definitions of inputs and outputs of LIF expressions. We study how the two relate and show that our syntactic definition is optimal in a sense that is made precise. The second contribution of this paper is a systematic study of the expressive power of sequential composition in LIF. Our results on composition tie in the results on inputs and outputs, and relate LIF to first-order logic (FO) and bounded-variable LIF to bounded-variable FO.

scholarly journals Identifying Bottlenecks in Practical SAT-Based Model Finding for First-Order Logic Ontologies with Datasets

2019 ◽  
Vol 33 ◽  
pp. 10039-10040
Author(s):  
Shirly Stephen ◽  
Torsten Hahmann
Keyword(s):  
Order Logic ◽  
First Order Logic ◽  
Propositional Satisfiability ◽  
First Order ◽  
Sat Solvers ◽  
Model Finding ◽  
Sat Solver

Satisfiability of first-order logic (FOL) ontologies is typically verified by translation to propositional satisfiability (SAT) problems, which is then tackled by a SAT solver. Unfortunately, SAT solvers often experience scalability issues when reasoning with FOL ontologies and even moderately sized datasets. While SAT solvers have been found to capably handle complex axiomatizations, finding models of datasets gets considerably more complex and time-intensive as the number of clause exponentially increases with increase in individuals and axiomatic complexity. We identify FOL definitions as a specific bottleneck and demonstrate via experiments that the presence of many defined terms of the highest arity significantly slows down model finding. We also show that removing optional definitions and substituting these terms by their definiens leads to a reduction in the number of clauses, which makes SAT-based model finding practical for over 100 individuals in a FOL theory.

scholarly journals A Clausal Normal Form Translation for FOOL

10.29007/ltkk ◽  
2018 ◽  
Author(s):  
Evgenii Kotelnikov ◽  
Laura Kovács ◽  
Martin Suda ◽  
Andrei Voronkov
Keyword(s):  
Normal Form ◽  
Programming Languages ◽  
Program Analysis ◽  
State Of The Art ◽  
Order Logic ◽  
Theorem Prover ◽  
First Order Logic ◽  
First Order ◽  
Theorem Provers ◽  
Superposition Calculus

Automated theorem provers for first-order logic usually operate on sets of first-order clauses. It is well-known that the translation of a formula in full first-order logic to a clausal normal form (CNF) can crucially affect performance of a theorem prover. In our recent work we introduced a modification of first-order logic extended by the first class boolean sort and syntactical constructs that mirror features of programming languages. We called this logic FOOL. Formulas in FOOL can be translated to ordinary first-order formulas and checked by first-order theorem provers. While this translation is straightforward, it does not result in a CNF that can be efficiently handled by state-of-the-art theorem provers which use superposition calculus. In this paper we present a new CNF translation algorithm for FOOL that is friendly and efficient for superposition-based first-order provers. We implemented the algorithm in the Vampire theorem prover and evaluated it on a large number of problems coming from formalisation of mathematics and program analysis. Our experimental results show an increase of performance of the prover with our CNF translation compared to the naive translation.

scholarly journals Superposition with First-class Booleans and Inprocessing Clausification

2021 ◽  
pp. 378-395
Author(s):  
Visa Nummelin ◽  
Alexander Bentkamp ◽  
Sophie Tourret ◽  
Petar Vukmirović
Keyword(s):  
State Of The Art ◽  
Higher Order ◽  
The State ◽  
Order Logic ◽  
Theorem Prover ◽  
First Order Logic ◽  
Higher Order Logic ◽  
First Order ◽  
Superposition Calculus

AbstractWe present a complete superposition calculus for first-order logic with an interpreted Boolean type. Our motivation is to lay the foundation for refutationally complete calculi in more expressive logics with Booleans, such as higher-order logic, and to make superposition work efficiently on problems that would be obfuscated when using clausification as preprocessing. Working directly on formulas, our calculus avoids the costly axiomatic encoding of the theory of Booleans into first-order logic and offers various ways to interleave clausification with other derivation steps. We evaluate our calculus using the Zipperposition theorem prover, and observe that, with no tuning of parameters, our approach is on a par with the state-of-the-art approach.

First-Order Logic Reasoning Support for the Semantic Web

2009 ◽  
Vol 19 (12) ◽  
pp. 3091-3099 ◽  
Author(s):  
Gui-Hong XU ◽  
Jian ZHANG
Keyword(s):  
Semantic Web ◽  
Order Logic ◽  
First Order Logic ◽  
First Order ◽  
Logic Reasoning

Boolean-valued structures

2018 ◽  
Author(s):  
Tim Button ◽  
Sean Walsh
Keyword(s):  
Model Theory ◽  
Order Logic ◽  
First Order Logic ◽  
Inference Rules ◽  
Mathematical Concepts ◽  
Semantic Framework ◽  
First Order ◽  
Standard Models ◽  
Boolean Valued Model ◽  
Semantic Values

Chapters 6-12 are driven by questions about the ability to pin down mathematical entities and to articulate mathematical concepts. This chapter is driven by similar questions about the ability to pin down the semantic frameworks of language. It transpires that there are not just non-standard models, but non-standard ways of doing model theory itself. In more detail: whilst we normally outline a two-valued semantics which makes sentences True or False in a model, the inference rules for first-order logic are compatible with a four-valued semantics; or a semantics with countably many values; or what-have-you. The appropriate level of generality here is that of a Boolean-valued model, which we introduce. And the plurality of possible semantic values gives rise to perhaps the ‘deepest’ level of indeterminacy questions: How can humans pin down the semantic framework for their languages? We consider three different ways for inferentialists to respond to this question.

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