We assume that there is not enough high-quality data to build a monolingual selectional preference model for the source language (shown by dotted lines).
we can use a bilingual vector space, that is, a semantic space in which words of both the source and the target language are represented, to translate each source language word s into the target language by identifying its nearest (most similar) target word tr(s): Now we can use a target language selectional preference model to obtain plausibilities for source triples: where the superscript indicates the language.