Abstract
We tackled the Evalita 2011 Domain Adaptation task with a strategy of active learning. The DeSR parser can be configured to provide different measures of perplexity in its own ability to parse sentences correctly. After parsing sentences in the target domain, a small number of the sentences with the highest perplexity were selected, revised manually and added to the training corpus in order to build a new parser model incorporating some knowledge from the target domain. The process was repeated a few times for building a new training resource partially adapted to the target domain. Using the new resource we trained three stacked parsers, and their combination was used to produce the final results.
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Attardi, G., Simi, M., Zanelli, A. (2013). Domain Adaptation by Active Learning. 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_9
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DOI: https://doi.org/10.1007/978-3-642-35828-9_9
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