Using Foreign Inclusion Detection to Improve Parsing Performance

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

• Type: Conference
• Year: 2007
• Where: EMNLP
• Authors: Beatrice Alex, Amit Dubey, Frank Keller
• Keywords: EMNLP 2007, English Inclusions, Inclusion Entity Model, Monolingual Parsers, Natural Language Processing