Understanding Natural Language
Understanding Natural Language
Preference semantics, ill-formedness, and metaphor
Computational Linguistics - Special issue on ill-formed input
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Automatic learning for semantic collocation
ANLC '92 Proceedings of the third conference on Applied natural language processing
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
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The paper claims that the right attachment rules for phrases originally suggested by Frazier and Fodor are wrong, and that none of the subsequent patchings of the rules by syntactic methods have improved the situation. For each rule there are perfectly straightforward and indefinitely large classes of simple counter-examples. We then examine suggestions by Ford et al., Schubert and Hirst which are quasi-semantic in nature and which we consider ingenious but unsatisfactory. We point towards a straightforward solution within the framework of preference semantics, set out in detail elsewhere, and argue that the principal issue is not the type and nature of information required to get appropriate phrase attachments, but the issue of where to store the information and with what processes to apply it.