Proceedings of the 33rd Annual Meeting of the Association of Computational Linguistics (ACL-95), pp. 335-337, Boston, MA, July 1995.
Paper ID: 45
Category: Natural Language Learning, Learning for Semantic Parsing
A system, WOLFIE, that acquires a mapping of words to their semantic representation is presented and a preliminary evaluation is performed. Tree least general generalizations (TLGGs) of the representations of input sentences are performed to assist in determining the representations of individual words in the sentences. The best guess for a meaning of a word is the TLGG which overlaps with the highest percentage of sentence representations in which that word appears. Some promising experimental results on a non-artificial data set are presented.
