Using Distributed Patterns as Language Independent Lexical Representations
Annette McElligott · 1993
While it is possible to construct Machine Translation (MT) systems of surprising sophistication using the technique of transfer between augmented parse trees (Brockmann, 1991) few people would doubt that in order to perform a fully satisfactory translation it will ultimately be necessary to work with meaning representations. However, there are many problems with developing a computationally tractable representation scheme for linguistic meanings either at the sentential (propositional) or lexical levels. One approach to the problem of capturing meanings at the lexical level is to use a form of distributed representation where each word meaning is converted into a point in an n-dimensional space (Sutcliffe, 1992a). Such representations can capture a wide variety of word meanings within the same formalism. In addition they can be used within distributed representations for capturing higher level information such as that expressed by sentences (SutcliiTe, 1991a). Moreover, they can be scaled to suit a particular tradeoff of specificity and memory usage (Sutcliffe, 1991b). Finally, distributed representations can be processed conveniently by vector processing methods or connectionist algorithms and can be used either as part of a symbolic system (Sutcliffe, 1992b) or within a connectionist architecture (Sutcliffe, 1988). A further point of interest regarding distributed representations for nouns is that they can be extracted automatically from machine readable dictionaries. As is well known, dictionaries contain much taxonomic information (Amsler, 1984). This information can be extracted automatically by parsing the dictionary definitions and extracting taxonomic pointers from them in a recursive fashion. For example both Vossen (1990) and Guthrie et al. (1990) constructed exhaustive taxonomies for the Longmans Dictionary of Contemporary English in this way. We have shown one manner in which it is possible to traverse such a taxonomy determining both the features germane to a particular concept and their appropriate centralities (strengths). In the present work we have taken this idea further by showing how lexicons different languages can be mapped into the same feature space thus allowing lexical translation between those languages.