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Constituent and dependency parsing, the two classic forms of syntacticparsing, have been found to benefit from joint training and decoding under auniform formalism, Head-driven Phrase Structure Grammar (HPSG). However,decoding this unified grammar has a higher time complexity ($O(n^5)$) thandecoding either form individually ($O(n^3)$) since more factors have to beconsidered during decoding. We thus propose an improved head scorer that helpsachieve a novel performance-preserved parser in $O$($n^3$) time complexity.Furthermore, on the basis of this proposed practical HPSG parser, weinvestigated the strengths of HPSG-based parsing and explored the generalmethod of training an HPSG-based parser from only a constituent or dependencyannotations in a multilingual scenario. We thus present a more effective, morein-depth, and general work on HPSG parsing.

Head-driven Phrase Structure Parsing in O($n^3$) Time Complexity