The notion of stochastic lexicalized tree-adjoining g rammar (SLTAG) is formally defined. The parameters of a SLTAG correspond to the probability of combining two structures each one associated with a word. The characteristics of SLTAG are unique and novel since it is lexieally sensitive (as N-gram models or Hidden Markov Models) and yet hierarchical (as stochastic context-free grammars) . Then...

We consider pairs of context-free tree grammars combined through synchronous rewriting. The resulting formalism is at least as powerful as synchronous tree adjoining grammars and linear, nondeleting macro tree transducers, while the parsing complexity remains polynomial. Its power is subsumed by context-free hypergraph grammars. The new formalism has an alternative characterization in terms of ...

Multiple (simple) context-free tree grammars are investigated, where “simple” means “linear and nondeleting”. Every multiple context-free tree grammar that is finitely ambiguous can be lexicalized; i.e., it can be transformed into an equivalent one (generating the same tree language) in which each rule of the grammar contains a lexical symbol. Due to this transformation, the rank of the nonterm...

Restricting the input or the output of a grammar-induced translation to a given set of trees plays an important role in statistical machine translation. The problem for practical systems is to find a compact (and in particular, finite) representation of said restriction. For the class of synchronous treeadjoining grammars, partial solutions to this problem have been described, some being restri...

We introduce synchronous tree adjoining grammars (TAG) into tree-to-string translation, which converts a source tree to a target string. Without reconstructing TAG derivations explicitly, our rule extraction algorithm directly learns tree-to-string rules from aligned Treebank-style trees. As tree-to-string translation casts decoding as a tree parsing problem rather than parsing, the decoder sti...

In this article, we introduce eXtensible MetaGrammar (XMG), a framework for specifying tree-based grammars such as Feature-Based Lexicalised Tree-Adjoining Grammars (FB-LTAG) and Interaction Grammars (IG). We argue that XMG displays three features which facilitate both grammar writing and a fast prototyping of tree-based grammars. Firstly, XMG is fully declarative. For instance, it permits a de...

We show how parsing of trees can be formalized in terms of the intersection of two tree languages. The focus is on weighted regular tree grammars and weighted tree adjoining grammars. Potential applications are discussed, such as parameter estimation across formalisms.

We show how preex probabilities can be computed for stochastic linear indexed grammars (SLIGs). Our results apply as well to stochastic tree-adjoining grammars (STAGs), due to their equivalence to SLIGs.

vVe show how prefix probabilities can be computed for stochastic linear indexed grammars (SLIGs). Our results apply as weil to stochastic tree-adjoining grammars (STAGs), due to their equivalence to SLIGs.