Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication - Volume 19, Issue 1, 2013

We report on TExSIS, a flexible bilingual terminology extraction system that uses a sophisticated chunk-based alignment method for the generation of candidate terms, after which the specificity of the candidate terms is determined by combining several statistical filters. Although the set-up of the architecture is largely language-independent, we present terminology extraction results for four different languages and three language pairs. Gold standard data sets were created for French-Italian, French-English and French-Dutch, which allowed us not only to evaluate precision, which is common practice, but also recall. We compared the TExSIS approach, which takes a multilingual perspective from the start, with the more commonly used approach of first identifying term candidates monolingually and then aligning the source and target terms. A comparison of our system with the LUIZ approach described by Vintar (2010) reveals that TExSIS outperforms LUIZ both for monolingual and bilingual terminology extraction. Our results also clearly show that the precision of the alignment is crucial for the success of the terminology extraction. Furthermore, based on the observation that the precision scores for bilingual terminology extraction outperform those of the monolingual systems, we conclude that multilingual evidence helps to determine unithood in less related languages.

EcoLexicon is a terminological knowledge base (TKB) on the environment which seeks to enhance both cognitive and communicative needs of different users. In order to achieve this, TKBs should reflect conceptual structures in a similar way to how concepts relate in the human mind (Meyer et al. 1992). Categorization itself is a dynamic context-dependent process. Therefore, representation and acquisition of specialized knowledge should certainly focus on contextual variation. In EcoLexicon, such contextualization takes the form of dynamic information modules, such as conceptual networks, images, textual information, and terminological variance. Recontextualization provides a way of representing the dynamic and multidimensional nature of conceptualization processes in the mind. On the one hand, it offers a qualitative criterion for the representation of specialized concepts in line with the workings of the human conceptual system. On the other hand, it provides a quantitative solution to the problem of information overload, as it significantly reduces irrelevant context-free information.

The existing language of oliviculture and elaiotechnics makes evident the significant development of this specialised field over the past decades. The progressive industrialisation and professionalization of this sector has progressively given rise to a new terminology that is updating the old jargon and is undergoing important normalisation processes. The present work focuses on the normalisation of the designations and definitions of olive oil categories. We also consider the usefulness of such actions and evaluate the differences between the currently marketed types of olive oil in order to reduce the difficulties in their analysis, classification, control and marketing. This study finally brings forward a denominative and definitional proposal for olive oil categories based on the theoretical assumptions of the project Olivaterm. Our proposal is directed at making information clear to the consumer as well as at facilitating the retrieval of specialised knowledge.

Companies must translate their content if they want to operate multinationally. Both quality and speed of translation are key factors in determining market share in the target market. Proactively managing terminology, including pre-translating key terms for a translation project, has beneficial effects on these factors. However, in commercial environments, the volumes of content and subsequently of the required terminology are typically large. Therefore, integrating terminology into the translation pipeline requires a process that is as automated as possible. Term extraction is the cornerstone of this process, but to maximize efficiency it requires a post-processing strategy that repurposes existing lexical resources. Terms extracted from corpora and subsequently translated should be channeled into the company termbase so that they can be leveraged for other purposes. These and other effective practices for processing extracted terms are discussed, based on the author’s experiences in one large company.

This paper addresses the issue of terms, namely Latin American, Hispanic and Latino, whose definitions are affected by social, economic, historical and ideological factors and which are at the crossroads of two or more disciplines. Definitions will be provided, using the Merriam-Webster for American English, the Oxford Dictionary for British English, and the Diccionario de la Real Academia for Spanish. The concept of ethnicity, introduced by the US Census Office in the 1970s to identify the Hispanic minority, will also be dealt with. The next section will examine the preferred choices of usage in academic journals in two broad areas, the Social Sciences on the one hand, and the Medical and Nursing professions on the others. It covers a total of 58 academic papers from two distinct periods, 2000–2005 and 2006–2010, in order to establish whether the terms are used consistently in the two broad areas, and whether there are major differences in use in the two time spans. The paper will conclude with a discussion of the findings, a reference to other activities that can be affected by the ambiguities of the definitions, and suggestions for further research.