Using WordNet for Building WordNets

This paper summarises a set of methodologies and techniques for the fast construction of multilingual WordNets. The English WordNet is used in this approach as a backbone for Catalan and Spanish WordNets and as a lexical knowledge resource for several subtasks.Comment: 8 pages, postscript file. In workshop on Usage of WordNet in NL

Combining Multiple Methods for the Automatic Construction of Multilingual WordNets

This paper explores the automatic construction of a multilingual Lexical Knowledge Base from preexisting lexical resources. First, a set of automatic and complementary techniques for linking Spanish words collected from monolingual and bilingual MRDs to English WordNet synsets are described. Second, we show how resulting data provided by each method is then combined to produce a preliminary version of a Spanish WordNet with an accuracy over 85%. The application of these combinations results on an increment of the extracted connexions of a 40% without losing accuracy. Both coarse-grained (class level) and fine-grained (synset assignment level) confidence ratios are used and evaluated. Finally, the results for the whole process are presented.Comment: 7 pages, 4 postscript figure

Extending the Galician Wordnet Using a Multilingual Bible Through Lexical Alignment and Semantic Annotation

In this paper we describe the methodology and evaluation of the expansion of Galnet - the Galician wordnet - using a multilingual Bible through lexical alignment and semantic annotation. For this experiment we used the Galician, Portuguese, Spanish, Catalan and English versions of the Bible. They were annotated with part-of-speech and WordNet sense using FreeLing. The resulting synsets were aligned, and new variants for the Galician language were extracted. After manual evaluation the approach presented a 96.8% accuracy

Word-sense disambiguated multilingual Wikipedia corpus

This article presents a new freely available trilingual corpus (Catalan, Spanish, English) that contains large portions of the Wikipedia and has been automatically enriched with linguistic information. To our knowledge, this is the largest such corpus that is freely available to the community: In its present version, it contains over 750 million words. The corpora have been annotated with lemma and part of speech information using the open source library FreeLing. Also, they have been sense annotated with the state of the art Word Sense Disambiguation algorithm UKB. As UKB assignsWordNet senses, andWordNet has been aligned across languages via the InterLingual Index, this sort of annotation opens the way to massive explorations in lexical semantics that were not possible before. We present a first attempt at creating a trilingual lexical resource from the sense-tagged Wikipedia corpora, namely, WikiNet. Moreover, we present two by-products of the project that are of use for the NLP community: An open source Java-based parser for Wikipedia pages developed for the construction of the corpus, and the integration of the WSD algorithm UKB in FreeLing.Peer ReviewedPostprint (published version

Predicate Matrix: an interoperable lexical knowledge base for predicates

183 p.La Matriz de Predicados (Predicate Matrix en inglés) es un nuevo recurso léxico-semántico resultado de la integración de múltiples fuentes de conocimiento, entre las cuales se encuentran FrameNet, VerbNet, PropBank y WordNet. La Matriz de Predicados proporciona un léxico extenso y robusto que permite mejorar la interoperabilidad entre los recursos semánticos mencionados anteriormente. La creación de la Matriz de Predicados se basa en la integración de Semlink y nuevos mappings obtenidos utilizando métodos automáticos que enlazan el conocimiento semántico a nivel léxico y de roles. Asimismo, hemos ampliado la Predicate Matrix para cubrir los predicados nominales (inglés, español) y predicados en otros idiomas (castellano, catalán y vasco). Como resultado, la Matriz de predicados proporciona un léxico multilingüe que permite el análisis semántico interoperable en múltiples idiomas

Knowledge Representation and WordNets

Knowledge itself is a representation of “real facts”. Knowledge is a logical model that presents facts from “the real world” witch can be expressed in a formal language. Representation means the construction of a model of some part of reality. Knowledge representation is contingent to both cognitive science and artificial intelligence. In cognitive science it expresses the way people store and process the information. In the AI field the goal is to store knowledge in such way that permits intelligent programs to represent information as nearly as possible to human intelligence. Knowledge Representation is referred to the formal representation of knowledge intended to be processed and stored by computers and to draw conclusions from this knowledge. Examples of applications are expert systems, machine translation systems, computer-aided maintenance systems and information retrieval systems (including database front-ends).knowledge, representation, ai models, databases, cams

Methodology and evaluation of the Galician WordNet expansion with the WN-Toolkit

In this paper the methodology and a detailed evaluation of the results of the expansion of the Galician WordNet using the WN-Toolkit are presented. This toolkit allows the creation and expansion of wordnets using the expand model. In our experiments we have used methodologies based on dictionaries and parallel corpora. The evaluation of the results has been performed both in an automatic and in a manual way, allowing a comparison of the precision values obtained with both evaluation procedures. The manual evaluation provides details about the source of the errors. This information has been very useful for the improvement of the toolkit and for the correction of some errors in the reference WordNet for Galician.En este artículo se presenta la metodología utilizada en la expansión del WordNet del gallego mediante el WN-Toolkit, así como una evaluación detallada de los resultados obtenidos. El conjunto de herramientas incluido en el WN-Toolkit permite la creación o expansión de wordnets siguiendo la estrategia de expansión. En los experimentos presentados en este artículo se han utilizado estrategias basadas en diccionarios y en corpus paralelos. La evaluación de los resultados se ha realizado de manera tanto automática como manual, permitiendo así la comparación de los valores de precisión obtenidos. La evaluación manual también detalla la fuente de los errores, lo que ha sido de utilidad tanto para mejorar el propio WN-Toolkit, como para corregir los errores del WordNet de referencia para el gallego.En aquest article es presenta la metodologia utilitzada en l'expansió del WordNet del gallec mitjançant el WN-Toolkit, així com una avaluació detallada dels resultats obtinguts. El conjunt d'eines inclòs en el WN-Toolkit permet la creació o expansió de wordnets seguint l'estratègia d'expansió. En els experiments presentats en aquest article s'han utilitzat estratègies basades en diccionaris i en corpus paral·lels. L'avaluació dels resultats s'ha realitzat de manera tant automàtica com a manual, permetent així la comparació dels valors de precisió obtinguts. L'avaluació manual també detalla la font dels errors, la qual cosa ha estat d'utilitat tant per millorar el propi WN-Toolkit, com per corregir els errors del WordNet de referència per al gallec

Experiments on applying relaxation labeling to map multilingual hierarchies

This paper explores the automatic construction of a multilingual Lexical Knowledge Base from preexisting lexical resources. This paper presents a new approach for linking already existing hierarchies. The Relaxation labeling algorithm is used to select --among all the candidate connections proposed by a bilingual dictionary-- the right conection for each node in the taxonomy.Postprint (published version

Acquiring Domain-Specific Knowledge for WordNet from a Terminological Database

In this research we explore a terminological database (Termoteca) in order to expand the Portuguese and Galician wordnets (PULO and Galnet) with the addition of new synset variants (word forms for a concept), usage examples for the variants, and synset glosses or definitions. The methodology applied in this experiment is based on the alignment between concepts of WordNet (synsets) and concepts described in Termoteca (terminological records), taking into account the lexical forms in both resources, their morphological category and their knowledge domains, using the information provided by the WordNet Domains Hierarchy and the Termoteca field domains to reduce the incidence of polysemy and homography in the results of the experiment. The results obtained confirm our hypothesis that the combined use of the semantic domain information included in both resources makes it possible to minimise the problem of lexical ambiguity and to obtain a very acceptable index of precision in terminological information extraction tasks, attaining a precision above 89% when there are two or more different languages sharing at least one lexical form between the synset in Galnet and the Termoteca record