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| + | ====== Keith Hall: Multilingual Dependency Parsing ====== | ||
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| + | 23. 10. 2006 | ||
| + | Keith Hall (Center for Language and Speech Processing, Johns Hopkins | ||
| + | University, USA) | ||
| + | Multilingual Dependency Parsing and Applications | ||
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| + | [[ http:// | ||
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| + | Abstract: Dependency parsing has recently come to the forefront of | ||
| + | interest in the statistical parsing community, culminating in the 2006 | ||
| + | CoNLL shared task on multilingual dependency parsing. Many of the | ||
| + | competing teams made use of the Maximum Spanning Tree (MST) approach | ||
| + | pioneered by McDonald and Ribarov (McDonald et al. '05). | ||
| + | A disadvantage of the MST approach is that it requires structural scores | ||
| + | to be derived from parent-child links. This constrains the parsing models | ||
| + | to be based on very local structure; disallowing the explicit modeling of | ||
| + | subcategorization and valency as well as far simpler constraints (compound | ||
| + | adjectives, etc.). | ||
| + | In this talk, I present a two-stage dependency parser which combines a | ||
| + | K-best MST algorithm with a reranker. The advantage of such an approach is | ||
| + | that the model used by the reranker includes features defined over entire | ||
| + | tree structures. I present empirical results showing that " | ||
| + | appear in the first 50 hypotheses generated by the heavily constrained MST | ||
| + | models. Furthermore, | ||
| + | the state-of-the-art parsers. Results are presented for a subset of the | ||
| + | CoNLL competition languages as well as English. | ||
| + | Finally, I will introduce a framework for the application of dependency | ||
| + | parsing to tasks such as Speech Reconstruction and parsing of | ||
| + | resource-poor languages. | ||
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