What to Do When Lexicalization Fails: Parsing German with Suffix Analysis and Smoothing

Proceedings of the 43rd Annual Meeting of the ACL, pages 314–321, Ann Arbor, June 2005. c⃝2005 Association for Computational Linguistics What to do when lexicalization fails: parsing German with suffix analysis and smoothing Amit Dubey University of Edinburgh Amit.Dubey@ed.ac.uk Abstract In this paper, we present an unlexical- ized parser for German which employs smoothing and suffix analysis to achieve a labelled bracket F-score of 76.2, higher than previously reported results on the NEGRA corpus. In addition to the high accuracy of the model, the use of smooth- ing in an unlexicalized parser allows us to better examine the interplay between smoothing and parsing results. 1 Introduction Recent research on German statistical parsing has shown that lexicalization adds little to parsing per- formance in German (Dubey and Keller, 2003; Beil et al., 1999). A likely cause is the relative produc- tivity of German morphology compared to that of English: German has a higher type/token ratio for words, making sparse data problems more severe. There are at least two solutions to this problem: first, to use better models of morphology or, second, to make unlexicalized parsing more accurate. We investigate both approaches in this paper. In particular, we develop a parser for German which at- tains the highest performance known to us by mak- ing use of smoothing and a highly-tuned suffix ana- lyzer for guessing part-of-speech (POS) tags from the input text. Rather than relying on smoothing and suffix analysis alone, we also utilize treebank transformations (Johnson, 1998; Klein and Man- ning, 2003) instead of a grammar induced directly from a treebank. The organization of the paper is as follows: Sec- tion 2 summarizes some important aspects of our treebank corpus. In Section 3 we outline several techniques for improving the performance of unlex- icalized parsing without using smoothing, including treebank transformations, and the use of suffix anal- ysis. We show that suffix analysis is not helpful on the treebank grammar, but it does increase per- formance if used in combination with the treebank transformations we present. Section 4 describes how smoothing can be incorporated into an unlexicalized grammar to achieve state-of-the-art results in Ger- man. Rather using one smoothing algorithm, we use three different approaches, allowing us to compare the relative performance of each. An error analy- sis is presented in Section 5, which points to several possible areas of future research. We follow the er- ror analysis with a comparison with related work in Section 6. Finally we offer concluding remarks in Section 7. 2 Data The parsing models we present are trained and tested on the NEGRA corpus (Skut et al., 1997), a hand- parsed corpus of German newspaper text containing approximately 20,000 sentences. It is available in several formats, and in this paper, we use the Penn Treebank (Marcus et al., 1993) format of NEGRA. The annotation used in NEGRA is similar to that used in the English Penn Treebank, with some dif- ferences which make it easier to annotate German syntax. German’s flexible word order would …

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