Objective evaluation of inferred context-free grammars

Author

Smith, Tony C. ; Witten, Ian H. ; Cleary, John ; Legg, Shane

Author_Institution

Dept. of Comput. Sci., Waikato Univ., Hamilton, New Zealand

fYear

1994

fDate

29 Nov-2 Dec 1994

Firstpage

392

Lastpage

396

Abstract

An infinite number of context-free grammars may be inferred from a given training set. The defensibility of any single grammar hinges on the ability to compare that grammar against others in a meaningful way. In keeping with the minimum description length principle, smaller grammars are preferred over larger ones, but only insofar as the small grammar does not over-generalise the language being studied. Furthermore, measures of size must incorporate the grammar´s ability to cover sentences of the source language not included in the training set. This paper describes a method for evaluating the quality of context-free grammars according to (i) the complexity of each grammar and (ii) the amount of disambiguation information necessary for much grammar to reproduce the training set. The sum of the two evaluations is used as an objective measure of a grammar´s information content. Three grammars are used as examples of this process

Keywords

context-free grammars; context-free languages; inference mechanisms; defensibility; disambiguation information; grammar complexity; grammar quality; inferred context-free grammars; information content; language generalization; minimum description length principle; objective evaluation; size measures; source language sentences; training set; Computer science; Convergence; Fasteners; Gold; Inference algorithms; Inference mechanisms; Mars;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Systems,1994. Proceedings of the 1994 Second Australian and New Zealand Conference on

Conference_Location

Brisbane, Qld.

Print_ISBN

0-7803-2404-8

Type

conf

DOI

10.1109/ANZIIS.1994.396995

Filename

396995