Bootstrapping a neural net dependency parser for German using CLARIN resources
نویسنده
چکیده
Statistical dependency parsers have quickly gained popularity in the last decade by providing a good trade-off between parsing accuracy and parsing speed. Such parsers usually rely on handcrafted symbolic features and linear discriminative classifiers to make attachment choices. Recent work replaces these with dense word embeddings and neural nets with great success for parsing English and Chinese. In the present work, we report on our experiences with neural net dependency parsing for German using CLARIN data.
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