An overview of portuguese wordnets

Semantic relations between words are key to building systems that aim to understand and manipulate language. For En- glish, the “de facto” standard for representing this kind of knowledge is Princeton’s WordNet. Here, we describe the wordnet-like resources currently available for Portuguese: their origins, methods of creation, sizes, and usage restrictions. We start tackling the problem of comparing them, but only in quantitative terms. Finally, we sketch ideas for potential collaboration between some of the projects.(undefined

As Wordnets do Português

Series: "Oslo Studies in Language". ISSN 1890-9639. 7(1), 2015.Not many years ago it was usual to comment on the lack of an open lexical- semantic knowledge base, following the lines of Princeton WordNet, but for Portuguese. Today, the landscape has changed significantly, and re- searchers that need access to this specific kind of resource have not one, but several alternatives to choose from. The present article describes the wordnet-like resources currently available for Portuguese. It provides some context on their origin, creation approach, size and license for utilization. Apart from being an obvious starting point for those looking for a computational resource with information on the meaning of Portuguese words, this article describes the resources available, compares them and lists some plans for future work, sketching ideas for potential collaboration between the projects described.CLUPFundação para a Ciência e a Tecnologia (FCT

The Lexical Grid: Lexical Resources in Language Infrastructures

Language Resources are recognized as a central and strategic for the development of any Human Language Technology system and application product. they play a critical role as horizontal technology and have been recognized in many occasions as a priority also by national and spra-national funding a number of initiatives (such as EAGLES, ISLE, ELRA) to establish some sort of coordination of LR activities, and a number of large LR creation projects, both in the written and in the speech areas

Challenges for the Multilingual Web of Data

The Web has witnessed an enormous growth in the amount of semantic information published in recent years. This growth has been stimulated to a large extent by the emergence of Linked Data. Although this brings us a big step closer to the vision of a Semantic Web, it also raises new issues such as the need for dealing with information expressed in different natural languages. Indeed, although the Web of Data can contain any kind of information in any language, it still lacks explicit mechanisms to automatically reconcile such information when it is expressed in ifferent languages. This leads to situations in which data expressed in a certain language is not easily accessible to speakers of other languages. The Web of Data shows the potential for being extended to a truly multilingual web as vocabularies and data can be published in a language-independent fashion, while associated language-dependent (linguistic) information supporting the access across languages can be stored separately. In this sense, the multilingual Web of Data can be realized in our view as a layer of services and resources on top of the existing Linked Data infrastructure adding i) linguistic information for data and vocabularies in different languages, ii) mappings between data with labels in different languages, and iii) services to dynamically access and traverse Linked Data across different languages. In this article we present this vision of a multilingual Web of Data. We discuss challenges that need to be addressed to make this vision come true and discuss the role that techniques such as ontology localization, ontology mapping, and cross-lingual ontology-based information access and presentation will play in achieving this. Further, we propose an initial architecture and describe a roadmap that can provide a basis for the implementation of this vision

Introduction: Modeling, Learning and Processing of Text-Technological Data Structures

Researchers in many disciplines, sometimes working in close cooperation, have been concerned with modeling textual data in order to account for texts as the prime information unit of written communication. The list of disciplines includes computer science and linguistics as well as more specialized disciplines like computational linguistics and text technology. What many of these efforts have in common is the aim to model textual data by means of abstract data types or data structures that support at least the semi-automatic processing of texts in any area of written communication

Enriching Ontologies with Multilingual Information

This paper presents a novel approach to ontology localization with the objective of obtaining multilingual ontologies. Within the ontology development process, ontology localization has been defined as the activity of adapting an ontology to a concrete linguistic and cultural community. Depending on the ontology layers – terminological and/or conceptual – involved in the ontology localization activity, three heterogeneous multilingual ontology metamodels have been identified, of which we propose one of them. Our proposal consists in associating the ontology metamodel to an external model for representing and structuring lexical and terminological data in different natural languages. Our model has been called Linguistic Information Repository (LIR). The main advantages of this modelling modality rely on its flexibility by allowing (1) the enrichment of any ontology element with as much linguistic information as needed by the final application, and (2) the establishment of links among linguistic elements within and across different natural languages. The LIR model has been designed as an ontology of linguistic elements and is currently available in Web Ontology Language (OWL). The set of lexical and terminological data that it provides to ontology elements enables the localization of any ontology to a certain linguistic and cultural universe. The LIR has been evaluated against the multilingual requirements of the Food and Agriculture Organization of the United Nations in the framework of the NeOn project. It has proven to solve multilingual representation problems related to the establishment of well-defined relations among lexicalizations within and across languages, as well as conceptualization mismatches among different languages. Finally, we present an extension to the Ontology Metadata Vocabulary, the so-called LexOMV, with the aim of reporting on multilinguality at the ontology metadata level. By adding this contribution to the LIR model, we account for multilinguality at the three levels of an ontology: data level, knowledge representation level and metadata level

Challenges for the multilingual Web of Data

Garcia J, Montiel-Ponsoda E, Cimiano P, Gómez-Pérez A, Buitelaar P, McCrae J. Challenges for the multilingual Web of Data. Journal of Web Semantics: Science, Services and Agents on the World Wide Web. 2012;11:63-71

Philipp Cimiano; Christian Chiarcos; John P. McCrae; Jorge Gracia (2020). Linguistic Linked Data. Representation, Generation and Applications. Springer International Publishing

Recensão de: Philipp Cimiano; Christian Chiarcos; John P. McCrae; Jorge Gracia (2020). Linguistic Linked Data. Representation, Generation and Applications. Springer International Publishing. ISBN 978-3-030-30225-

Investigating the universality of a semantic web-upper ontology in the context of the African languages

Ontologies are foundational to, and upper ontologies provide semantic integration across, the Semantic Web. Multilingualism has been shown to be a key challenge to the development of the Semantic Web, and is a particular challenge to the universality requirement of upper ontologies. Universality implies a qualitative mapping from lexical ontologies, like WordNet, to an upper ontology, such as SUMO. Are a given natural language family's core concepts currently included in an existing, accepted upper ontology? Does SUMO preserve an ontological non-bias with respect to the multilingual challenge, particularly in the context of the African languages? The approach to developing WordNets mapped to shared core concepts in the non-Indo-European language families has highlighted these challenges and this is examined in a unique new context: the Southern African languages. This is achieved through a new mapping from African language core concepts to SUMO. It is shown that SUMO has no signi ficant natural language ontology bias.ComputingM. Sc. (Computer Science

Database Models and Data Formats

The deliverable describes data structure and XML formats that have been investigated and defined for data representation of linguistic and semantic resources underlying the KYOTO system