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Human Affairs
|
2015
|
vol. 25
|
issue 3
327-341
EN
Writing an article isn’t a straightforward process. It involves difficult decisions, dilemmas and even politics, and these have a substantial effect on article quality and impact. This is even more true now than used to be the case due to the massification of science and pressure to publish. The author explores six common dilemmas and offers guidance on how to deal with them: a) why we should (not) write at all; b) which language to choose-English, the national language or another suitable language; c) how to credit resources in times of resource abundance; d) how to deal with authorship disputes; e) whether to write clearly and concisely or to represent the “messy reality” as closely as possible; and f) which journal to choose.
EN
In this paper we propose a modeling of contextual information around a terminological unit, for the needs of a scientific writing aid tool in the biomedical field. We focus more specifically on the modeling of significant phraseic contexts that we formalize as semantically characterized argument patterns. This modeling is based on a large corpus of biomedical scientific articles and relay on semantic types specified in a domain ontology, Unified Medical Language System.
PL
Autorki proponują modelizacje informacji kontekstualnej wokół leksemów specjalistycznych w celu wypracowania systemu wspomagania redagowania prac naukowych w dziedzinie biomedycyny. Pod uwagę brana jest tu modelizacja kontekstu zdaniowego opisanego jako schematy aktantowe, które maja charakter semantyczny. Modelizacja ta opiera się na obszernym korpusie artykułów naukowych z biomedycyny, a także na Typach Semantycznych ontologii danej dziedziny, Unified Medical Language System.
FR
Dans cet article nous proposons une modélisation de l’information contextuelle autour des lexies spécialisées en vue de l’élaboration d’un système d’aide à la rédaction scientifique dans le domaine biomédical. Nous considérons plus spécifiquement la modélisation du contexte phrastique décrit en termes de schémas actantiels que nous caractérisons sémantiquement. Cette modélisation est fondée sur un grand corpus d’articles scientifiques dans le domaine biomédical. Elle s’appuie également sur les Types Sémantiques d’une ontologie du domaine, Unified Medical Language System.
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