Leveraging Multilingual Training for Limited Resource Event Extraction

COLING 2016 Andrew HsiYiming YangJaime CarbonellRuochen Xu

Event extraction has become one of the most important topics in information extraction, but to date, there is very limited work on leveraging cross-lingual training to boost performance. We propose a new event extraction approach that trains on multiple languages using a combination of both language-dependent and language-independent features, with particular focus on the case where target domain training data is of very limited size... (read more)

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