Dependency Trees and the Strong Generative Capacity of CCG

We propose a novel algorithm for extracting dependencies from the derivations of a large fragment of CCG. Unlike earlier proposals, our dependency structures are always tree-shaped. We then use these dependency trees to compare the strong generative capacities of CCG and TAG and obtain surprising results: Both formalisms generate the same languages of derivation trees --- but the mechanisms they use to bring the words in these trees into a linear order are incomparable.

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