Language acquisition: learning phrases in context
Machine learning: a guide to current research
Strategies in language acquisition: learning phrases in context
Strategies in language acquisition: learning phrases in context
The self-extending phrasal lexicon
Computational Linguistics - Special issue of the lexicon
TINLAP '75 Proceedings of the 1975 workshop on Theoretical issues in natural language processing
Towards a self-extending lexicon
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Disambiguation and language acquisition through the phrasal lexicon
COLING '86 Proceedings of the 11th coference on Computational linguistics
Learning word meanings by instruction
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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The hierarchical lexicon, in contrast to the traditional flat lexicon, enables a linguistic model to perform even in situations of incomplete knowledge: when a specific entry is missing, a more general entry can cover the gap. The question still remains regarding the construction of the lexicon itself. Since the lexicon is organized as a hierarchy, and not as a flat structure, phrases cannot simply be placed in the lexicon: they must be interconnected with other phrases in the hierarchy at the appropriate level of generality. Furthermore, since input examples arc always given in terms of specific phrases, phrases must be propagated up and down the hierarchy, starting at the bottom level. In this paper we describe a learning algorithm which is based on two existing machine-learning models: learning in a version space [Mitchell82], and learning by accumulating specific episodes in a dynamic memory [Kolodner84, Schank82]. The input required by the algorithm is a sequence of specific episodes, or training examples, from which lexical entries at various levels in the hierarchy arc generalized and specialized. The algorithm is embodied by the program RINA [Zernik87b] which models learning English phrases by a second language speaker.