We introduce a MetaGrammar, which allows us to automatically generate, from a single and compact MetaGrammar hierarchy, parallel Lexical Functional Grammars (LFG) and Tree-Adjoining Grammars (TAG) for French and for English: the grammar writer specifies in compact manner syntactic properties that are potentially framework-, and to some extent language-independent (such as subcategorization, valency alternations and realization of syntactic functions), from which grammars for several frameworks and languages are automatically generated offline.

We present a rule--based shallow--parser compiler, which allows to generate a robust shallow-parser for any language, even in the absence of training data, by resorting to a very limited number of rules which aim at identifying constituent boundaries. We contrast our approach to other approaches used for shallow--parsing (i.e. finite-state and probabilistic methods). We present an evaluation of our tool for English (Penn Treebank) and for French (newspaper corpus "LeMonde") for several tasks (NP-chunking & "deeper" parsing).

Since Kimball (73) parsing preference principles such as "Right association" (RA) and "Minimal attachment" (MA) are often formulated with respect to constituent trees. We present 3 preference principles based on "derivation trees" within the framework of LTAGs. We argue they remedy some shortcomings of the former approaches and account for widely accepted heuristics (e.g. argument/modifier, idioms...).