Data-oriented parsing with discontinuous constituents and function tags

Statistical parsers are effective but are typically limited to producing projective dependencies or constituents. On the other hand, linguistically rich parsers recognize non-local relations and analyze both form and function phenomena but rely on extensive manual grammar engineering. We combine advantages of the two by building a statistical parser that produces richer analyses. We investigate new techniques to implement treebank-based parsers that allow for discontinuous constituents. We present two systems. One system is based on a Linear Context-Free Rewriting System (LCFRS), while using a Probabilistic Discontinuous Tree-Substitution Grammar (PDTSG) to improve disambiguation performance. Another system encodes discontinuities in the labels of phrase-structure trees, allowing for efficient context-free grammar parsing. The two systems demonstrate that tree fragments as used in treesubstitution grammar improve disambiguation performance Chile capturing non-local relations on an as-needed basis. Additionally, we present results for models that produce function tags, resulting in a more linguistically adequate model of the data. We report substantial accuracy improvements in discontinuous parsing for German, English, and Dutch, including results on spoken Dutch.