The Surprising Variance in Shortest-Derivation Parsing

We investigate full-scale shortest-derivation parsing (SDP), wherein the parser selects an analysis built from the fewest number of training fragments. Shortest derivation parsing exhibits an unusual range of behaviors. At one extreme, in the fully unpruned case, it is neither fast nor accurate. At the other extreme, when pruned with a coarse unlexicalized PCFG, the shortest derivation criterion becomes both fast and surprisingly effective, rivaling more complex weighted-fragment approaches. Our analysis includes an investigation of tie-breaking and associated dynamic programs. At its best, our parser achieves an accuracy of 87% F1 on the English WSJ task with minimal annotation, and 90% F1 with richer annotation.

• Type: Journal
• Year: 2011
• Where: ACL
• Authors: Mohit Bansal, Dan Klein
• Keywords: ACL 2011, Computational Linguistics, Derivation, Dynamic Programs, Sdp