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AceWiki: A Natural and Expressive Semantic Wiki
, 2008
"... We present AceWiki, a prototype of a new kind of semantic wiki using the controlled natural language Attempto Controlled English (ACE) for representing its content. ACE is a subset of English with a restricted grammar and a formal semantics. The use of ACE has two important advantages over existing ..."
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We present AceWiki, a prototype of a new kind of semantic wiki using the controlled natural language Attempto Controlled English (ACE) for representing its content. ACE is a subset of English with a restricted grammar and a formal semantics. The use of ACE has two important advantages over existing semantic wikis. First, we can improve the usability and achieve a shallow learning curve. Second, ACE is more expressive than the formal languages of existing semantic wikis. Our evaluation shows that people who are not familiar with the formal foundations of the Semantic Web are able to deal with AceWiki after a very short learning phase and without the help of an expert.
Controlled English for Reasoning on the Semantic Web
, 2009
"... The existing Semantic Web languages have a very technical focus and fail to provide good usability for users with no background in formal methods. We argue that controlled natural languages like At-tempto Controlled English (ACE) can solve this problem. ACE is a sub-set of English that can be tran ..."
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Cited by 3 (1 self)
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The existing Semantic Web languages have a very technical focus and fail to provide good usability for users with no background in formal methods. We argue that controlled natural languages like At-tempto Controlled English (ACE) can solve this problem. ACE is a sub-set of English that can be translated into various logic based languages, among them the Semantic Web standards OWL and SWRL. ACE is accompanied by a set of tools, namely the parser APE, the Attempto Reasoner RACE, the ACE View ontology and rule editor, the semantic wiki AceWiki, and the Protune policy framework. The applications cover a wide range of Semantic Web scenarios, which shows how broadly ACE can be applied. We conclude that controlled natural languages can make the Semantic Web better understandable and more usable. 1.1 Why Use Controlled Natural Languages for the Semantic Web? The Semantic Web proves to be quite challenging for its developers: there is the problem of adequately representing domain knowledge, there is the question of the interoperability of heterogeneous knowledge bases, there is the need for reliable and efficient reasoning, and last but not least the Semantic Web requires generally acceptable user interfaces. Languages like RDF, OWL, SWRL, RuleML, R2ML, SPARQL etc. have been developed to meet the challenges of the Semantic Web. The developers of these languages are predominantly researchers with a strong background in logic. This is reflected in the languages, all of which have syntaxes that conspicuously show their logic descent. Domain experts and end-users, however, often do not have a background in logic. They shy away from logic notations, and prefer to use notations familiar to them — which is usually natural language possibly complemented by diagrams, tables, and formulas.
Business Process Evolution: a Rule-based Approach
"... Business Process (BP) evolution is a key aspect of BP lifecycle. There are several reasons that may cause BP modifications. Among these, particularly important are the changes of the enterprise organization and operation strategies, which can be captured by business rules (BRs). We focus here on a B ..."
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Business Process (BP) evolution is a key aspect of BP lifecycle. There are several reasons that may cause BP modifications. Among these, particularly important are the changes of the enterprise organization and operation strategies, which can be captured by business rules (BRs). We focus here on a BP-based enterprise that, in addition to the enterprise BPs, is also regulated by a set of BRs: such BPs and BRs need to be globally consistent (and have to be maintained consistent after any changes). In this paper we present an ontological approach capable of representing BRs and BPs in a coherent way. Then, our objective is twofold: (i) clarifying the intended meaning of a BR that (when firstly formulated) may have more than one interpretation; (ii) identifying all processes in the BP repository that are (or have become) inconsistent with the BRs and thus need to be changed to reestablish the overall consistency.
Paraphrasing controlled English texts
- In Proc. CNL’2009 (CEUR Workshop Proceedings
"... Abstract. We discuss paraphrasing controlled English texts, by defining two fragments of Attempto Controlled English (ACE): Core ACE and NP ACE. We show that these fragments have features that one would usually expect from paraphrases. We also describe a tool that paraphrases ACE sentences into thes ..."
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Abstract. We discuss paraphrasing controlled English texts, by defining two fragments of Attempto Controlled English (ACE): Core ACE and NP ACE. We show that these fragments have features that one would usually expect from paraphrases. We also describe a tool that paraphrases ACE sentences into these fragments. 1
Discourse-Based Reasoning for Controlled Natural Languages
"... Abstract. Logic-based controlled natural languages usually provide some facility for compositional representation, minimally including sentence level coordination and sometimes subordination. Although these compositional forms suffice for representing short passages, they can become unwieldy for exp ..."
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Abstract. Logic-based controlled natural languages usually provide some facility for compositional representation, minimally including sentence level coordination and sometimes subordination. Although these compositional forms suffice for representing short passages, they can become unwieldy for expressing entire paragraphs and documents. This paper describes an approach to representing larger composite texts in a controlled natural language. This approach, called discourse-based reasoning, integrates rhetorical structure theory with argumentation theory to define a model for defining composite structures and argument strategies in an ontological representation. Rhetorical structures are used to represent controlled texts, and argument strategies are defined for reasoning about interactions between structures. This provides the basis for expressing, summarizing, and interacting with explanatory and argumentative discourse. This would expand the scope of problems that may be addressed using controlled natural languages.
Rhetorical Compositions for Controlled Natural Languages
"... Abstract. Logic-based controlled natural languages usually provide some facility for compositional representation, minimally including sentence level coordination and sometimes subordination. These forms of compositional representation are useful for expressing short passages of a few sentences, but ..."
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Abstract. Logic-based controlled natural languages usually provide some facility for compositional representation, minimally including sentence level coordination and sometimes subordination. These forms of compositional representation are useful for expressing short passages of a few sentences, but compared to natural language they offer only a limited range of expression, and they are unwieldy for expressing longer passages. This paper describes a method for bringing more naturalness to controlled natural languages. This approach defines a model for representing compositional structures found in natural language, such as Antithesis, Concession, and Unless in a way that is both rhetorically expressive and logically reducible. This is demonstrated through a series of examples using both natural and controlled natural language. The paper then describes a set of intercompositional rules of inference that can be used to reason about the interrelationships between compositional structures, facilitating the discovery and assessment of supportive and conflicting relationships among them. This ability to represent and discover interrelationships among discourse representation structures could be useful for developing applications that must not only follow a set of rules of inference, but reason about the rules themselves.
