Upper Bounds for Unsupervised Parsing with Unambiguous Non-Terminally Separated Grammars

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Abstract

Unambiguous Non-Terminally Separated (UNTS) grammars have properties that make them attractive for grammatical inference. However, these properties do not state the maximal performance they can achieve when they are evaluated against a gold treebank that is not produced by an UNTS grammar. In this paper we investigate such an upper bound. We develop a method to find an upper bound for the unlabeled F 1 performance that any UNTS grammar can achieve over a given treebank. Our strategy is to characterize all possible versions of the gold treebank that UNTS grammars can produce and to find the one that optimizes a metric we define. We show a way to translate this score into an upper bound for the F 1. In particular, we show that the F 1 parsing score of any UNTS grammar can not be beyond 82.2% when the gold treebank is the WSJ10 corpus.

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APA

Luque, F. M., & Infante-Lopez, G. (2009). Upper Bounds for Unsupervised Parsing with Unambiguous Non-Terminally Separated Grammars. In EACL 2009 - Proceedings of the EACL 2009 Workshop on Computational Linguistic Aspects of Grammatical Inference, CLAGI 2009 (pp. 58–65). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1705475.1705484

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