Neural dependency parser with biaffine attention and BERT embeddings
This resource contains the code of the dependency parser used in the paper: Do and Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited". The parser is a re-implementation of the neural dependency parser from Dozat and Manning (2017) and is extended to use the BERT language m...
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| Main Authors: | , |
|---|---|
| Format: | Database Research Data |
| Language: | English |
| Published: |
Heidelberg
Universität
2023-11-13
|
| DOI: | 10.11588/data/0U6IWL |
| Subjects: | |
| Online Access: | Resolving-System, kostenfrei, Volltext: https://doi.org/10.11588/data/0U6IWL Verlag, kostenfrei, Volltext: https://heidata.uni-heidelberg.de/dataset.xhtml?persistentId=doi:10.11588/data/0U6IWL Verlag, kostenfrei, Volltext: https://github.com/bichngocdo/bert-biaffine-parser |
| Author Notes: | Bich-Ngoc Do, Ines Rehbein |
MARC
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| 520 | |a This resource contains the code of the dependency parser used in the paper: Do and Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited". The parser is a re-implementation of the neural dependency parser from Dozat and Manning (2017) and is extended to use the BERT language model as input features. The pre-trained models on the German dataset of the SPMRL 2014 Shared Task used to report results in the paper are also included. | ||
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