Abstract
We present a novel way of extracting a categorial grammar from annotated data. Using the sentences from the Paris VII annotated treebank [2] as our starting point, we use a tree transducer to convert the annotated trees from the corpus into categorial grammar derivations.
We describe both the formal aspects and the implementation of the tree transducer, which is a conservative extension of standard tree transducers allowing a compact specification of the transductions rules relevant for our purposes, and we discuss the specific set of transduction rules we use to convert the corpus into AB grammar derivation trees.
Evaluating the resulting tree transducer on the entire corpus, we find that it produces a treebank finds lexical entries for 90,0% of the corpus, though it produces complete derivations for only 75% of all sentence in the corpus.
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Sandillon-Rezer, NF., Moot, R. (2011). Using Tree Transducers for Grammatical Inference. In: Pogodalla, S., Prost, JP. (eds) Logical Aspects of Computational Linguistics. LACL 2011. Lecture Notes in Computer Science(), vol 6736. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22221-4_16
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