Abstract
We evaluate two very different methods for domain adaptation of graph-based dependency parsers on the EVALITA 2011 Domain Adaptation data, namely instance-weighting [1] and self-training [2,3]. Since the source and target domains (newswire and law, respectively) were very similar, instance-weighting was unlikely to be efficient, but some of the semi-supervised approaches led to significant improvements on development data. Unfortunately, this improvement did not carry over to the released test data.
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Plank, B., Søgaard, A. (2013). Experiments in Newswire-to-Law Adaptation of Graph-Based Dependency Parsers. In: Magnini, B., Cutugno, F., Falcone, M., Pianta, E. (eds) Evaluation of Natural Language and Speech Tools for Italian. EVALITA 2012. Lecture Notes in Computer Science(), vol 7689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35828-9_8
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DOI: https://doi.org/10.1007/978-3-642-35828-9_8
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