Abstract
Dependency trees represent sentences as labeled directed graphs encoding syntactic relations between words. The labels on the arcs represent grammatical relations such as “subject”, “object”, various types of modifiers etc. Dependency trees capture grammatical structures that are easy to interpret and can be useful in several language processing tasks such as information extraction (Culotta and Sorensen, 2004), knowledge acquisition (Ciaramita et al., 2005), machine translation (Ding and Palmer, 2005) and information retrieval (Surdeanu et al., 2008). Dependency treebanks are becoming available in many languages. Several approaches to dependency parsing on multiple languages have been evaluated in the CoNLL 2006 and 2007 shared tasks (Buchholz and Marsi, 2006; Nivre et al., 2007), and in conjunction with semantic role labeling as a joint learning problem in the CoNLL 2008 shared task (Surdeanu et al., 2008).
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- 1.
The figure also contains entity annotations which will be explained below in Section 6.4.1.
- 2.
Available from http://desr.sourceforge.net
- 3.
By contrast, the version of the Penn Treebank used for the CoNLL 2007 shared task includes also non-projective representations.
- 4.
BBN Pronoun Coreference and Entity Type Corpus, 2005. Linguistic Data Consortium (LDC) catalog number LDC2005T33.
- 5.
BBN Corpus documentation.
- 6.
The full label for “ORG” is “ORG:Corporation”, and “WOA” stands for “WorkOfArt:Other”.
- 7.
The script is available from http://w3.msi.vxu.se/%7enivre/research/Penn2Malt.html
- 8.
- 9.
Tree Tagger is available from http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/
- 10.
The 1st-order parser takes 7 s (user time) to process Section 23.
- 11.
Available from sourceforge.net
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Acknowledgements
The first author would like to thank Thomas Hofmann for useful discussions concerning the issue of higher-order feature representations of Section 6.3.4. We would also like to thank Brian Roark and the editors for useful comments and references to related work.
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Ciaramita, M., Attardi, G. (2010). Dependency Parsing with Second-Order Feature Maps and Annotated Semantic Information. In: Bunt, H., Merlo, P., Nivre, J. (eds) Trends in Parsing Technology. Text, Speech and Language Technology, vol 43. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9352-3_6
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