Multilingual Language Resources Research Articles

Pristopi k izdelavi leksikalnih podatkovnih zbirk

The paper presents WordNet and EuroWordNet, lexical databases in which concepts are linked with lexical and semantic relations. In the past decade, similar lexical databases for other languages have been based on them, for which two approaches have mostly been used: the creation of independent wordnets and their subsequent integration into multilingual lexical databases, and the expansion of existing lexical databases into the target language by translating the entries and adopting relations between them. Due to the great automation potential of the network creation process and a uniform structure of the resulting databases, the latter approach has become very popular. This is why the given model was tested in this paper for its ability to create a Slovene wordnet, and the results were compared to its language-motivated counterpart acquired from the Fida corpus as well as other mono- and multilingual language resources for Slovene.

Language Resources – a Part of World Cultural Heritage

This article briefly reviews multilingual language resources for Bulgarian, developed in the frame of some international projects: the first-ever annotated Bulgarian MTE digital lexical resources, Bulgarian-Polish corpus, Bulgarian-Slovak parallel and aligned corpus, and Bulgarian-Polish-Lithuanian corpus. These resources are valuable multilingual dataset for language engineering research and development for Bulgarian language. The multilingual corpora are large repositories of language data with an important role in preserving and supporting the world's cultural heritage, because the natural language is an outstanding part of the human cultural values and collective memory, and a bridge between cultures.

Multilingual Online Resources for Minority Languages of a Campus Community

This paper discusses on an initiative of developing a repository on multilingual language resources for minority languages of a campus community. The choice of language is based on a survey amongst IIUM international students about the status of their mother language's resources and usages in the digital world. As a starting point, multilingual dictionaries of textual and speech for these identified languages are developed. This initiative is an effort to ensure that such minority languages will be protected from being endangered in this era of globalization.

Multilingual language resources and interoperability

This article introduces the topic of “Multilingual language resources and interoperability”. We start with a taxonomy and parameters for classifying language resources. Later we provide examples and issues of interoperatability, and resource architectures to solve such issues. Finally we discuss aspects of linguistic formalisms and interoperability.

Lexical systems: graph models of natural language lexicons

We introduce a new type of lexical structure called lexical system, an interoperable model that can feed both monolingual and multilingual language resources. We begin with a formal characterization of lexical systems as simple directed graphs, solely made up of nodes corresponding to lexical entities and links. To illustrate our approach, we present data borrowed from a lexical system that has been generated from the French DiCo database. We later explain how the compilation of the original dictionary-like database into a net-like one has been made possible. Finally, we discuss the potential of the proposed lexical structure for designing multilingual lexical resources.

Implantation d’un tri lexical respectant la particularité des noms propres

The computational treatment of multilingual language resources (as in the Prolex projet, cf (Grass et al. 2002)) should respect lexical conventions admitted by each language’s native speakers. These conventions may vary from one language to another, as in the case of alphabetical sorting algorithm. This algorithm must take a number of universal as well as language-dependent particularities into account, such as the distinction of upper- and lowercase letters, the sorting bi-directionality (from the left to the right or conversely), the role of diacritics (resulting either in variants of a letter, as é, è and ê in French, or in independent letters, as å in Danish or ą in Polish), the role of punctuation characters, the multi-character letters (as ch or ll in Spanish, or dzs in Hungarian) and the ligatures (as œ in French, or ß in German). We describe a Unicode-based sorting algorithm inspired by (LaBonté 1998) for proper names. In the particular case of the sorting of the proper names, three additional points are to be taken into account : the presence of numerical values (Arab numerals or Roman numerals), the variation of spelling of the ligatures and the permutation in the sorting of the multi-word units. Apart from the word list to be sorted, its input is a language-dependent code table which defines the language’s alphabet, the number of algorithm’s passes, the direction of each pass, and the order of letters or groups of letters in each pass. The implementation of the algorithm is done by a finite-state transducer which allows a fast assignment of sort keys to words. The algorithm proved correct for European languages such as English, French, and Polish, as well as for Thai. It outperforms other sorting algorithms, such as those implemented in Intex (Silberztein 1993) and Unitex (Paumier 2003) systems.

Multilingual Text Mining

The availability of a huge amount of textual data from a bewildering variety of sources leads to the well-identified paradox based on which an overload of information means no usable knowledge. In fact, up to 80% of electronic data is textual. Moreover, the most valuable information is encoded in pages which are written in various native languages, but are relevant even to non-native speakers. The process of accessing all these raw data, heterogeneous for language used, and transforming them into information is therefore inextricably linked to the concepts of textual analysis and synthesis, hinging greatly on the ability to master the problems of multilingualism. Through multilingual text mining, users can get an overview of great volumes of textual data having a highly readable grid, which helps them discover meaningful similarities among documents and find all related information. This paper describes the approach used by SYNTHEMA for multilingual text mining, showing the classification results on around 600 breaking news items written in English, Italian and French. 1 Multilingual resources construction Generally speaking, the manual construction and maintenance of multilingual language resources is undoubtedly expensive, requiring remarkable efforts. Being established in 1994 by computer scientists from the IBM Research Center, with the expertise and skills suited to provide effective software solutions, as well as carry out R&D in Natural Language Processing area, SYNTHEMA has been involved in Machine Translation, Information Extraction and Text Mining activities since 1996, primarily in the field of Technology Watch. The growing availability of comparable and parallel corpora has pushed SYNTHEMA to develop specific methods for semi-automatic updating of lexical resources. They are based on Natural Language Understanding and Machine Learning. These techniques detect multilingual lexicons from such corpora, by extracting all the © 2005 WIT Press WIT Transactions on Information and Communication Technologies, Vol 35, www.witpress.com, ISSN 1743-3517 (on-line) Data Mining VI 89