205 research outputs found
Extending, trimming and fusing WordNet for technical documents
This paper describes a tool for the automatic
extension and trimming of a multilingual
WordNet database for cross-lingual retrieval
and multilingual ontology building in
intranets and domain-specific document
collections. Hierarchies, built from
automatically extracted terms and combined
with the WordNet relations, are trimmed
with a disambiguation method based on the
document salience of the words in the
glosses. The disambiguation is tested in a
cross-lingual retrieval task, showing
considerable improvement (7%-11%). The
condensed hierarchies can be used as
browse-interfaces to the documents
complementary to retrieval
Meaningful results for Information Retrieval in the MEANING project
The goal of the MEANING project (IST-2001-34460) is to develop tools for the automatic acquisition of lexical knowledge that will help Word Sense Disambiguation (WSD). The acquired lexical knowledge from various sources and various languages is stored in the Multilingual Central Repository (MCR) (Atserias et al 04), which is based on the design of the EuroWordNet database. The MCR holds wordnets in various languages (English, Spanish, Italian, Catalan and Basque), which are interconnected via an Inter-Lingual-Index (ILI). In addition, the MCR holds a number of ontologies and domain labels related to al
Automatic sense clustering in EuroWordNet
This paper addresses ways in which we envisage to reduce the fine-grainedness of WordNet and express in a more systematic way the relations between its numerous sense distinctions. In the EuroWordNet project, we have distinguished various automatic methods for grouping senses into more coarse-grained sense groups. These resulting clusters reflect aspects of lexical organization, displaying a variety of semantic regularities or generalizations. In this way, the compatibility of the language-specific wordnets in the EuroWordNet multilingual knowledge base is increased
Enriching Ontologies with Multilingual Information
Organizations working in a multilingual environment demand multilingual ontologies. To solve this problem we propose LabelTranslator, a system that automatically localizes ontologies. Ontology localization consists of adapting an ontology to a concrete language and cultural community.
LabelTranslator takes as input an ontology whose labels are described in a source natural language and obtains the most probable translation into a target natural language of each ontology label. Our main contribution is the automatization of this process which reduces human efforts to localize an ontology manually. First, our system uses a translation service which obtains automatic translations of each ontology label (name of an ontology term) from/into English, German, or Spanish by consulting different linguistic resources such as lexical databases, bilingual dictionaries, and terminologies. Second, a ranking method is used to sort each ontology label according to similarity with its lexical and semantic context.
The experiments performed in order to evaluate the quality of translation show that our approach is a good approximation to automatically enrich an ontology with multilingual information
Web 2.0, language resources and standards to automatically build a multilingual named entity lexicon
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) building by taking into consideration three elements: (i) the knowledge available in existing LRs, (ii) the vast amount of information available from the collaborative paradigm that has emerged from the Web 2.0 and (iii) the use of standards to improve interoperability. We present a case study in which a set of LRs for diļ¬erent languages (WordNet for English and Spanish and Parole-Simple-Clips for Italian) are
extended with Named Entities (NE) by exploiting Wikipedia and the aforementioned LRs. The practical result is a multilingual NE lexicon connected to these LRs and to two ontologies: SUMO and SIMPLE. Furthermore, the paper addresses an important problem which aļ¬ects the Computational Linguistics area in the present, interoperability, by making use of the ISO LMF standard to encode this lexicon. The diļ¬erent steps of the procedure (mapping, disambiguation, extraction, NE identiļ¬cation and postprocessing) are comprehensively explained and evaluated. The resulting resource contains 974,567, 137,583 and 125,806 NEs for English, Spanish and Italian respectively. Finally, in order to check the usefulness of the constructed resource, we apply it into a state-of-the-art Question Answering system and evaluate its impact; the NE lexicon improves the systemās accuracy by 28.1%. Compared to previous approaches to build NE repositories, the current proposal represents a step forward in terms of automation, language independence, amount of NEs acquired and richness of the information represented
MEANING-full effects in information retrieval
This deliverable reports on testing the use and effect
of the integration of the MEANING technology in the
TwentyOne search engine of Irion
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