Abstract
We show that naïve modeling of morphosyntactic agreement in a Constituency-Based (CB) statistical parsing model is worse than none, whereas a linguistically adequate way of modeling inflectional morphology in CB parsing leads to improved performance. In particular, we show that an extension of the Relational-Realizational (RR) model that incorporates agreement features is superior to CB models that treat morphosyntax as state-splits (SP), and that the RR model benefits more from inflectional features. We focus on parsing Hebrew and report the best result to date, F184.13 for parsing off of gold-tagged text, 5% error reduction from previous results.
| Original language | English |
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| Pages | 40-48 |
| Number of pages | 9 |
| State | Published - 2010 |
| Externally published | Yes |
| Event | 1st Workshop on Statistical Parsing of Morphologically-Rich Languages, SPMRL 2010 - Los Angeles, United States Duration: 5 Jun 2010 → … |
Conference
| Conference | 1st Workshop on Statistical Parsing of Morphologically-Rich Languages, SPMRL 2010 |
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| Country/Territory | United States |
| City | Los Angeles |
| Period | 5/06/10 → … |
Bibliographical note
Publisher Copyright:© 2010 Association for Computational Linguistics
Funding
The work of the first author has been funded by NWO, grant 017.001.271. We wish to thank Joakim Nivre and three anonymous reviewers for helpful comments on earlier drafts. Acknowledgements The work of the first author has been funded by NWO, grant 017.001.271. We wish to thank Joakim Nivre and three anonymous reviewers for helpful comments on earlier drafts.
| Funders | Funder number |
|---|---|
| Joakim Nivre | |
| Nederlandse Organisatie voor Wetenschappelijk Onderzoek | 017.001.271 |