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We present a simple, data-driven approach to generation from knowledge bases (KB). A key feature of this approach is that grammar induction is driven by the extended domain of locality principle of TAG (Tree Adjoining Grammar); and that it takes into account both syntactic and semantic information. The resulting extracted TAG includes a unification based… (More)
This abstract describes a contribution to the 2013 KBGen Challenge from CNRS/LORIA and the University of Lor-raine. Our contribution focuses on an attempt to automate the extraction of a Feature Based Tree Adjoining Grammar equipped with a unification based compo-sitional semantics which can be used to generate from KBGen data.mars which link syntax and… (More)
We present a method for automatically generating descriptions of biological events encoded in the KB BIO 101 Knowledge base. We evaluate our approach on a corpus of 336 event descriptions, provide a qualitative and quantitative analysis of the results obtained and discuss possible directions for further work.