Ontologies, taxonomies, thesauri:learning from texts

The use of ontologies as representations of knowledge is widespread but their construction, until recently, has been entirely manual. We argue in this paper for the use of text corpora and automated natural language processing methods for the construction of ontologies. We delineate the challenges and present criteria for the selection of appropriate methods. We distinguish three ma jor steps in ontology building: associating terms, constructing hierarchies and labelling relations. A number of methods are presented for these purposes but we conclude that the issue of data-sparsity still is a ma jor challenge. We argue for the use of resources external tot he domain specific corpus.

'The prime minister said...': voices in translated political texts

A variety of texts are translated to fulfil functions for political communication across languages, cultures, and ideologies. For example, newspapers regularly provide quotes of statements by foreign politicians, without explicitly indicating that these politicians were actually speaking in their own languages. Politicians react to statements by other politicians as they were presented to them in translation. Political scientists and other experts often debate the potential political consequences of (the translation of) a statement. This chapter addresses the (in)visibility of translation in political communication and the link between textual profiles of translations and the socio-political contexts in which they are produced. The analyses are conducted from the perspective of Translation Studies. The focus is on institutionalised forms of political discourse, i.e. texts that originate in political or media institutions. The link between translation profiles and the social, institutional, ideological conditions of text production is illustrated with reference to authentic political texts (interviews, speeches by politicians, press conferences), mainly involving English, French and German as source and target languages.