Collocations in a Rule-Based MT System: A Case Study Evaluation of Their Translation Adequacy

Collocations constitute a subclass of multi-word expressions that are particularly problematic for machine translation, due 1) to their omnipresence in texts, and 2) to their morpho-syntactic properties, allowing virtually unlimited variation and leading to long-distance dependencies. Since existing MT systems incorporate mostly local information, these are arguably ill-suited for handling those collocations whose items are not found in close proximity. In this article, we describe an integrated environment in which collocations (and possibly their translation equivalents) are first identified from text corpora and stored in the lexical database of a translation system, then they are employed by this system, which is capable of dealing with syntactic transformations as it is based on a deep linguistic approach. We compare the performance of our system (in terms of collocation translation adequacy) with that of two major MT systems, one statistical, and the other rule-based. Our results confirm that syntactic variation affects translation quality and show that a deep syntactic approach is more robust in this sense, especially for languages with freer word order (e.g., German) and richer morphology (e.g., Italian) than English.