Learning Context-Free Grammars with a Simplicity Bias

We examine the role of simplicity in directing the induction of context-free grammars from sample sentences. We present a rational reconstruction of Wol 's SNPR { the Gridssystem { which incorporates a bias toward grammars that minimize description length. The algorithm alternates between merging existing nonterminal symbols and creating new symbols, using a beam search to move from complex to simpler grammars. Experiments suggest that this approach can induce accurate grammars and that it scales reasonably to more di cult domains.

• Type: Conference
• Year: 2000
• Where: ECML
• Authors: Pat Langley, Sean Stromsten
• Keywords: Context-free Grammars, ECML 2000, Grammars, Machine Learning, Simpler Grammars