In this paper, we use a feature model of the semantics of plural determiners to present an approach to grammar checking for definiteness. Using neural network techniques, a semantics -- morphological category mapping was learned. We then applied a textual encoding technique to the 125 occurences of the relevant category in a 10 000 word narrative text and learned a surface -- semantics mapping. By applying the learned generation function to the newly generated representations, we achieved a correct category assignment in many cases (87 %). These results are considerably better than a direct surface categorization approach (54 %), with a baseline (always guessing the dominant category) of 60 %. It is discussed, how these results could be used in multilingual NLP applications.
@article{arxiv.cmp-lg/9606017,
title = {With raised eyebrows or the eyebrows raised ? A Neural Network Approach to Grammar Checking for Definiteness},
author = {Gabriele Scheler},
journal= {arXiv preprint arXiv:cmp-lg/9606017},
year = {2008}
}