Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication - Volume 7, Issue 1, 2001

Research has traditionally portrayed language for specialized purposes (LSP) as devoid of idiosyncrasy, indeterminacy, context-specificity, inter-cultural variation, inconsistency of expression and acceptation, among other attributes associated with general or non-specialized discourse. This article suggests that attitudes and practices spawned by an uncritical reading of traditional LSP research could indeed constitute a hindrance to the adequate processing of specialized material by translators, terminologists and by ordinary readers or communication parties. The article shows that there is cultural-epistemic relativity in specialized discourses, and that indeterminacy/inconsistency of concepts and terms is present in specialized discourses just as in non-specialized material. These two theses are shown to have implications for the establishment of concept and term equivalence, such as is called for during translating, compilation of terminological resources, or even during reading/comprehension.

Two different reasons suggest that combining the performance of several term extractors could lead to an improvement in overall system accuracy. On the one hand, there is no clear agreement on whether to follow statistical, linguistic or hybrid approaches for (semi-) automatic term extraction. On the other hand, combining different knowledge sources (e.g. classifiers) has proved successful in improving the performance of individual sources on several NLP tasks (some of them closely related to or involved in term extraction), such as context-sensitive spelling correction, part-of-speech tagging, word sense disambiguation, parsing, text classification and filtering, etc.In this paper, we present a proposal for combining a number of different term extraction techniques in order to improve the accuracy of the resulting system. The approach has been applied to the domain of medicine for the Spanish language. A number of tests have been carried out with encouraging results.

The purpose of this article is to identify and classify metaphorical sign terms in the field of abdominal radiodiagnostic imaging. A 1,000,000 word electronic corpus of English and Spanish medical texts was used to compile an extensive list of metaphorical designations for signs detected on radiological images. These terms were classified thematically and structurally and analyzed from the terminological perspective of logical motivation. The fundamental premise behind this research is the belief that a better knowledge of this type of terminology (both English and Spanish) can lead to a better understanding of the specialist’s perception of the prototypical image conjured by the metaphor.

Bilingual machine readable dictionaries are important and indispensable resources of information for cross-language information retrieval, and machine translation. Recently, these cross-language informational activities have begun to focus on specific academic or technological domains. In this paper, we describe a bilingual dictionary acquisition system which extracts translations from non-parallel but comparable corpora of a specific academic domain and disambiguates the extracted translations. The proposed method is two-fold. At the first stage, candidate terms are extracted from a Japanese and English corpus, respectively, and ranked according to their importance as terms. At the second stage, ambiguous translations are resolved by selecting the target language translation which is the nearest in rank to the source language term. Finally, we evaluate the proposed method in an experiment.

This paper describes on-going work on the development of two complementary resources: WordMed® and Scriptum®. The former is a lexico-conceptual knowledge base (KB) comprising information from four medical sub-domains (diagnostics, procedures, tumors and medicines). This resource is only accessible for the language and domain expert in charge of supervising the knowledge acquisition and KB-updating processes. The latter resource, Scriptum®, is the user’s tool; it contains a medical KB, transferred from WordMed®, together with a viewer for the user to access the knowledge stored in the KB.

An HMM-based method for extracting bilingual morpheme pairs from domain-specific bilingual term lists is reported in this paper. In recent years, many bilingual term lists have become available in electronic form. If the bilingual morpheme pairs in the lists are automatically identified, they can be used as bootstrapping information for the automatic identification of bilingual term pairs in bilingual textual corpora. Or, they can be used for automatically extracting translation rules of complex terms. In our method, Japanese terms are segmented into morphemes while at the same time the corresponding Japanese-English morpheme pairs are identified. The advantage of our method is that it requires no pre-processing tool such as a morphological analyser. The result of the experiment was quite satisfactory, our method achieved well over 80% precision and recall.