Analogical Natural Language Processing

The use of examples as the basis for machine translation systems has gained considerable acceptance since the original proposal of Nagao in 1984. In this short book, Jones first reviews the fundamental principles of example-based machine translation (EBMT) in order to then introduce the specific mechanisms of his model. The key characteristic of this model is its purely stochastic processing, which is based on the algorithm put forth by Skousen (1989) in his Analogical Modeling strategy for language comprehension. Overall, the book is well-written and offers a good introduction to some of the very interesting problems of machine translation. But my reading left me somewhat unsatisfied. In order to explain this, let me first summarize the chapters. The goals and method of the work are clearly stated in the nine pages that form the introduction: Jones intends to demonstrate the possibility of uniformly using examples rather than rules for machine translation. I emphasize that, in this context, "the term 'analogy' refers to the general process of deriving information about some new piece of language by comparison with known piece(s) of language" (p. 4). Also, it is important to understand that "the rejection of rule-based natural language processing does not mean that linguistic representations cannot be used" (p. 5). Indeed, Jones subscribes to a non-inferential heavily-predicated representational strategy based on Functional Grammar. Within this framework, "source language predications and their target language equivalents are stored as instantiated examples of translation, the source half of which attempt to clone themselves onto the source language input . . . . The translations are achieved by generating the target language half of the best matching example into a surface realization . . . . Where only partial cloning is being achieved across a set of examples, the process of recombination can be used to recombine elements of example predications based on the results of the analogical modelling" (p. 6). The second chapter provides some additional background material on EBMT, as well as a partial survey of relevant research. Depth is typically privileged over breadth. For example, Functional Grammar seems to reduce exclusively to the work of Dik (1978) and van der Korst (1989), with the consequence that some details are mentioned but not explained, or discussed at length and then never revisited in the rest of the book. Chapter 3 then overviews the proposed model, and more specifically, the representations it uses. Very quickly the reader discovers complex hand-coded frames littered with the primitives of Functional Grammar, as well as somewhat artificial examples from a narrow domain. Thus, the usual criticism against complex innate (nay, ad hoc) data structures soon comes to mind. Jones does motivate the use of Functional Grammar for machine translation and raises lots of interesting questions for MT. But