Interchanging lexical resources on the Semantic Web

Lexica and terminology databases play a vital role in many NLP applications, but currently most such resources are published in application-specific formats, or with custom access interfaces, leading to the problem that much of this data is in ‘‘data silos’’ and hence difficult to access. The Semantic Web and in particular the Linked Data initiative provide effective solutions to this problem, as well as possibilities for data reuse by inter-lexicon linking, and incorporation of data categories by dereferencable URIs. The Semantic Web focuses on the use of ontologies to describe semantics on the Web, but currently there is no standard for providing complex lexical information for such ontologies and for describing the relationship between the lexicon and the ontology. We present our model, lemon, which aims to address these gap

Lemon: An Ontology-Lexicon model for the Multilingual Semantic Web.

The Monnet project offers a solution to this cross-language information access problem by using a novel combination of Machine Translation and Semantic Web Technology. Monnet business users will be able to have transparent access to company information across national and linguistic boundaries. Monnet public services users will find answers to their questions independent of the country's official languages. A key solution to this problem is to deal with the information at a semantic level. Monnet achieves this through semantically aware term translation based on a novel approach that integrates ontology-based domain semantics with linguistic information from the domain lexicon. The Monnet solution will change the way business and government provide, exchange and integrate information, driving global standardization efforts

Dynamics of solitons in the one-dimensional nonlinear Schrödinger equation

We investigate bright solitons in the one-dimensional Schrödinger equation in the framework of an extended variational approach. We apply the latter to the stationary ground state of the system as well as to coherent collisions between two or more solitons. Using coupled Gaussian trial wave functions, we demonstrate that the variational approach is a powerful method to calculate the soliton dynamics. This method has the advantage that it is computationally faster compared to numerically exact grid calculations. In addition, it goes far beyond the capability of analytical ground state solutions, because the variational approach provides the ability to treat excited solitons as well as dynamical interactions between different wave packets. To demonstrate the power of the variational approach, we calculate the stationary ground state of the soliton and compare it with the analytical solution showing the convergence to the exact solution. Furthermore, we extend our calculations to nonstationary solitons by investigating coherent collisions of several wave packets in both the low- and high-energy regime. Comparisons of the variational approach with numerically exact simulations on grids reveal excellent agreement in the high-energy regime while deviations can be observed for low energies

Squeezing lemon with GATE

International audienceAn increasing number of enterprises are beginning to include ontologies into Text Analytics (TA) applications. This can be challenging for a TA group wishing to avail of such technologies due to the manual effort needed to map language resources within a TA system for a new domain. Ontology lexicalization offers a solution to this problem by seeking to automatically generate lexical resources in order to shrink the manual effort of this conceptto-text mapping process. However, conventional approaches are limited in that they often can only generate term mentions of proper noun, personal noun or fixed key phrases from concept labels in ontologies. Such approaches do not generalize to cope with more complex concept mentions such as nominal compounds or multi-word expressions. An alternative consideration is lemon-Lexicon Model for Ontologies which offers a more sophisticated solution to this problem. We describe a simple use case for exploiting lemon within a widely used open-source TA framework and demonstrate how lemon generated lexical resources are at least comparable in agreement to OntoRootGazeteer, a conventional ontology lexicalization approach

Interchanging lexical resources on the Semantic Web

McCrae J, Aguado-de-Cea G, Buitelaar P, et al. Interchanging lexical resources on the Semantic Web. Language Resources and Evaluation. 2012;46(4):701-719

Ontology-based Multilingual Access to Financial Reports for Sharing Business Knowledge across Europe

Declerck T, Krieger H-U, Thomas SM, et al. Ontology-based Multilingual Access to Financial Reports for Sharing Business Knowledge across Europe. In: Roóz J, Ivanyos J, eds. Internal Financial Control Assessment Applying Multilingual Ontology Framework. Budapest: HVG Press Kft.; 2010: 67-76

Interchanging lexical resources on the semantic web

Lexica and terminology databases play a vital role in many NLP applications, but currently most such resources are published in application-specific formats, or with custom access interfaces, leading to the problem that much of this data is in "data silos" and hence difficult to access. The Semantic Web and in particular the Linked Data initiative provide effective solutions to this problem, as well as possibilities for data reuse by inter-lexicon linking, and incorporation of data categories by dereferencable URIs. The Semantic Web focuses on the use of ontologies to describe semantics on the Web, but currently there is no standard for providing complex lexical information for such ontologies and for describing the relationship between the lexicon and the ontology. We present our model, lemon, which aims to address these gaps while building on existing work, in particular the Lexical Markup Framework, the ISOcat Data Category Registry, SKOS (Simple Knowledge Organization System) and the LexInfo and LIR ontology-lexicon models