Ontology-Based Controlled Natural Language Editor Using CFG with Lexical Dependency

Namgoong, Hyun; Kim, Hong-Gee

doi:10.1007/978-3-540-76298-0_26

Cited by 11 publications

(8 citation statements)

References 8 publications

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“…Furthermore, a larger sample size was chosen and more controls for bias were implemented. All evaluation material and data are available online for inspection, including the CLOnE evaluation results for comparison 16 . The evaluation contained the following:…”

Section: Methodsmentioning

confidence: 99%

“…In addition, GINO was not compared to any existing Ontology editor during the evaluation. Finally, [16] present an Ontology based Controlled Natural Language Editor, similar to GINO, which uses CFG(Context-free grammar) and lexical dependencies -CFG-DL to generate RDF triples. To our knowledge the system ports only to RDF and does not cater for other Ontology languages.…”

Section: Related Workmentioning

confidence: 99%

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RoundTrip Ontology Authoring

Davis

Iqbal

Funk

et al. 2008

Lecture Notes in Computer Science

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Abstract. Controlled Language (CL) for Ontology Editing tools offer an attractive alternative to naive users, wishing to create Ontologies. However despite the benefits of CLs, users are still required to learn the correct syntactic structures in order to use the Controlled Language properly. Referring to CL vocubulary/syntax rules can be time consuming, annoying and in certain cases may prevent uptake of the tool. This paper extends work based on a controlled language for ontology editingCLOnE, which uses standard NLP tools, for processing the language and manipulating an ontology. The reversal of this process involves text generation of the CLOnE language from an existing ontology using Natural Language Generation (NLG), specifically template based/shallow NLG. The text generator and the CLOnE authoring process both combine to form a RoundTrip Ontology Authoring environment: one can start with an existing imported ontology or one originally produced using CLOnE, (re)produce the Controlled Language using the NL generator, modify or edit the text as required and subsequently parse the text back into the ontology using the CLOnE environment. Building on previous methodology we undertook an evaluation, comparing the Round Trip Ontology Authoring process with a well-known ontology editor; Where previous work required a CL reference manual with several examples in order to use the controlled language, the substitution of NLG reduces this learning curve for users, while simultaneously improving upon existing results for basic Ontology editing tasks.

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Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

RoundTrip Ontology Authoring

Davis

Iqbal

Funk

et al. 2008

Lecture Notes in Computer Science

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“…Thus, after running the Sesame, locally or in a server, we are ready to upload our data, as .N3 format. [8], [9], [10] In this way a successful upload guarantee that our data are stored and ready for consuming by other people. For this purpose we are offering a SPARQL endpoint as one of the best practices for consuming the data.…”

Section: Storing Rdf Triplesmentioning

confidence: 98%

“…At the moment there is a relatively large list of choices for this purpose, where each of them has its advantages and disadvantages. Among these, the most know tools are AllegroGraph 7 , OpenLink Virtuoso 8 , Sesame 9 , 4store 10 , etc. For some practical reasons, in this project our choice has been Sesame, which includes parsing, storing, inferencing and querying such data.…”

Section: Storing Rdf Triplesmentioning

confidence: 99%

Expansion of a relational database to support semantic web queries

Januzaj¹,

Krrabaj²,

Luma³

et al. 2017

Pressacademia

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Nowadays various types of data, especially those with public character, are stored and represented in relational databases. While this way of storing data is a practice for most of the institutions, it turns them into isolated silos with low level of accessibility and interoperability in the web. Indeed not all datasets are readable from the World Wide Web, therefore to increase their access it is necessary to provide mapping from relational databases to any serialization format of Resource Description Framework (RDF), as one of the best practices for distributing and interlinking data on the web. While there are several ways to accomplish the mapping process, the most appropriate and fastest way is by using the Protégé Plugins application. In this paper we present this mapping method, and describe the complete conversion of a database from SQL Server relational Database to RDF using different scenarios. By using Sesame Repository, as the local repository for our dataset, several SPARQL queries will be generated on top of our data. As a main contribution this paper emphasizes the advantages and performance of querying and using serialized RDF statements versus those stored in the relational databases.

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“…Several platforms have been developed to function as either natural language ontology editors or natural language query systems. Two good examples in the first category are CNL Editor [ 34 ] (formerly OntoPath [ 35 ]) and GINO [ 36 ]. OntoPath is in fact situated in the frontier between these two categories because it manages and creates RDF ontologies, and it is also capable of defining queries from natural language sentences.…”

Section: Introductionmentioning

confidence: 99%

Using Data Crawlers and Semantic Web to Build Financial XBRL Data Generators: The SONAR Extension Approach

Rodríguez-García

Rodríguez-González

Colomo‐Palacios

et al. 2014

The Scientific World Journal

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Precise, reliable and real-time financial information is critical for added-value financial services after the economic turmoil from which markets are still struggling to recover. Since the Web has become the most significant data source, intelligent crawlers based on Semantic Technologies have become trailblazers in the search of knowledge combining natural language processing and ontology engineering techniques. In this paper, we present the SONAR extension approach, which will leverage the potential of knowledge representation by extracting, managing, and turning scarce and disperse financial information into well-classified, structured, and widely used XBRL format-oriented knowledge, strongly supported by a proof-of-concept implementation and a thorough evaluation of the benefits of the approach.

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Ontology-Based Controlled Natural Language Editor Using CFG with Lexical Dependency

Cited by 11 publications

References 8 publications

RoundTrip Ontology Authoring

RoundTrip Ontology Authoring

Expansion of a relational database to support semantic web queries

Using Data Crawlers and Semantic Web to Build Financial XBRL Data Generators: The SONAR Extension Approach

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