Terminological databases do not always provide detailed information on the linguistic behaviour of terms, although this is important for potential users such as translators or students. In this paper we describe a project that aims to fill this gap by proposing a method for annotating terms in sentences based on that developed within the FrameNet project (Ruppenhofer et al. 2010) and by implementing it in an online resource called DiCoInfo. We focus on the methodology we devised, and show with some preliminary results how similar actantial (i.e. argumental) structures can provide evidence for defining lexical relations in specific languages and capturing cross-linguistic equivalents. The paper argues that the syntactico-semantic annotation of the contexts in which the terms occur allows lexicographers to validate their intuitions concerning the linguistic behaviour of terms as well as interlinguistic relations between them. The syntactico-semantic annotation of contexts could, therefore, be considered a good starting point in terminology work that aims to describe the linguistic functioning of terms and offer a sounder basis to define interlinguistic relationships between terms that belong to different languages.

Multilingual terminological resources do not always include the equivalents of specialized verbs that occur in legal texts. This study aims to bridge that gap by proposing a methodology to assign the equivalents of this kind of predicative units. We use a comparable corpus of judgments produced by the Supreme Court of Canada and by the Supremo Tribunal de Justiça de Portugal. From this corpus, 200 English and Portuguese verbs are selected. The description of the verbs is based on the theory of Frame Semantics (Fillmore 1977, 1977, 1982, 1985) as well as on the FrameNet methodology (Ruppenhofer et al. 2010). Specialized verbs are said to evoke a semantic frame, a sort of conceptual scenario in which a number of mandatory elements play specific roles (e.g. the role of judge, the role of defendant). Given that semantic frames are language independent to a fair degree (Boas 2005; Baker 2009), the labels attributed to each of the 76 identified frames (e.g. [Crime], [Regulations]) were used to group together 165 pairs of candidate equivalents. 71% of them are full equivalents, whereas 29% are only partial equivalents.