Paper: Single Malt or Blended? A Study in Multilingual Parser Optimization

ACL ID D07-1097
Title Single Malt or Blended? A Study in Multilingual Parser Optimization
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

We describe a two-stage optimization of the MaltParser system for the ten languages in the multilingual track of the CoNLL 2007 shared task on dependency parsing. The first stage consists in tuning a single-parser system for each language by optimizing pa- rameters of the parsing algorithm, the fea- ture model, and the learning algorithm. The second stage consists in building an ensem- ble system that combines six different pars- ing strategies, extrapolating from the opti- mal parameters settings for each language. When evaluated on the official test sets, the ensemble system significantly outperforms the single-parser system and achieves the highest average labeled attachment score.