DFKI-LT - Eficiency in Unification-Based N-best Parsing
Eficiency in Unification-Based N-best Parsing
1 Trends in Parsing Technology: Dependency Parsing, Domain Adaptation, and Deep Parsing volume 43,
Text, Speech and Language Technology Series,
We extend a recently proposed algorithm for n-best unpacking of parse forests to deal efficiently with (a) Maximum Entropy (ME) parse selection models containing important classes of non-local features, and (b) forests produced by uni- fication grammars containing significant proportions of globally inconsistent analy- ses. The new algorithm empirically exhibits a linear relationship between processing time and the number of analyses unpacked at all degrees of ME feature non-locality; in addition, compared with agenda-driven best-first parsing and exhaustive parsing with post-hoc parse selection it leads to improved parsing speed, coverage, and ac- curacy.