Paper: Surface Realisation from Knowledge-Bases

ACL ID P14-1040
Title Surface Realisation from Knowledge-Bases
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014

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 ex- tended domain of locality principle of TAG (Tree Adjoining Grammar); and that it takes into account both syntactic and semantic information. The resulting ex- tracted TAG includes a unification based semantics and can be used by an existing surface realiser to generate sentences from KB data. Experimental evaluation on the KBGen data shows that our model outper- forms a data-driven generate-and-rank ap- proach based on an automatically induced probabilistic grammar; and is comparable with a handcrafted symbolic approach.