Papers by Johannes Gontrum
Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing - A Tale of Two Parsers Revisited (D19-1)
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| Challenge: | In recent years, dependency parsing has shifted from discrete features to neural networks and continuous representations. |
| Approach: | They propose to use deep contextualized word embeddings to pack information about global sentence structure into local feature representations to make the two approaches virtually equivalent in terms of accuracy and error profile. |
| Outcome: | The proposed model improves the accuracy and error profile of transition-based and graph-based dependency parsers on 13 languages. |