A computer implementation of Russian derivational morphology represented in DATR
Prof Greville G. Corbett Dr Norman M. Fraser Dr Andrew Hippisley
Period of award
September 1992 - September 1995
Not all morphological processes are equally productive. The English suffix -ness productively derives nouns from adjectives, as in good > goodness, whereas the suffix -th is limited to warmth and a few others. In a theory of morphology that is built around defaults, this difference in the productivity of different derivational processes can be expressed by making -ness available as a default to all adjectives, while exceptions like -th can be made to override the default.
The facts of derivation in Russian can be dealt with in a similar way, though they are somewhat more complex in their detail. This project was designed to address the complex nature of derivation in Russian through a formally explicit account of a substantial fragment of its word-stock, encoded in such a way that it could be computationally checked. The formalism chosen was DATR (Evans and Gazdar 1989), a lexical knowledge representation language that is computable, and captures lexical knowledge in terms of default inheritance structures.