This paper defines a method for lexicon in the biomedical domain from comparable corpora. The methodis based on compositionaltranslation and exploits morpheme-level translation equivalences. It can generate translations for a large variety of morphologicallyconstructed words and can also generate ’fertile’ translations. We show that fertile translations increase the overall quality of the extracted lexicon for English to French translation.
 We propose a method for compiling bilingual terminologies of multi-word terms (MWTs) for given translation pairs of seed terms. Traditional methods for bilingual terminology compilation exploit parallel texts, while the more recent ones have focused on comparable corpora. We use bilingual corpora collected from the web and tailor made for the seed terms. For each language, we extract from the corpus a set of MWTs pertaining to the seed’s semantic domain, and use a compositional method to align MWTs from both sets. We increase the coverage of our system by using thesauri and by applying a bootstrap method. Experimental results show high precision and indicate promising prospects for future developments. The automatic compilation of bilingual lists of terms from specialized comparable corpora using lexical alignment has been successful for single-word terms (SWTs), but remains disappointing for multi-word terms (MWTs). The low frequency and the variability of the syntactic structures of MWTs in the source and the target languages are the main reported problems. This paper defines a general framework dedicated to the lexical alignment of MWTs from comparable corpora that includes a compositional translation process and the standard lexical context analysis. The compositional method which is based on the translation of lexical items being restrictive, we introduce an extended compositional method that bridges the gap between MWTs of different syntactic structures through morphological links. We experimented with the two compositional methods for the French–Japanese alignment task. The results show a significant improvement for the translation of MWTs and advocate further morphological analysis in lexical alignment. The WWW is two orders of magnitude larger than the largest corpora. Although noisy, web text presents language as it is used, and statistics derived from the Web can have practical uses in many NLP applications. For this reason, the WWW should be seen and studied as any other computationally available linguistic resource. In this article, we illustrate this by showing that an Example-Based approach to lexical choice for machine translation can use the Web as an adequate and free resource.