Paper: Using Foreign Inclusion Detection to Improve Parsing Performance

ACL ID D07-1016
Title Using Foreign Inclusion Detection to Improve Parsing Performance
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

Inclusions from other languages can be a significant source of errors for monolin- gual parsers. We show this for English in- clusions, which are sufficiently frequent to present a problem when parsing German. We describe an annotation-free approach for accurately detecting such inclusions, and de- velop two methods for interfacing this ap- proach with a state-of-the-art parser for Ger- man. An evaluation on the TIGER cor- pus shows that our inclusion entity model achieves a performance gain of 4.3 points in F-score over a baseline of no inclusion de- tection, and even outperforms a parser with access to gold standard part-of-speech tags.