Abstract. Syntactic disambiguators for natural language often use ”Treebank Grammars”: probabilistic grammars which are directly projected from an annotated corpus. In this paper we show that for describing these systems in the framework of Estimation Theory, we must generalize this theory so that it allows for an infinite number of parameters. Embracing this generalization will also bring the justification of statistical smoothing techniques within the scope of Estimation Theory. 1