Abstract
In this chapter, we describe an approach that enriches the feature representations for a graph-based model using a dependency language model (DLM) (Shen et al. 2008).The N-gram DLM has the ability to predict the next child based on the N − 1 immediate previous children and their head.
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Notes
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We ensure that the text used for extracting subtrees do not include the sentences of the Penn Treebank.
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We exclude the sentences of the CTB data from the Gigaword data.
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Chen, W., Zhang, M. (2015). Training with Dependency Language Models. In: Semi-Supervised Dependency Parsing. Springer, Singapore. https://doi.org/10.1007/978-981-287-552-5_8
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DOI: https://doi.org/10.1007/978-981-287-552-5_8
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