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: | , |
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| Format: | Database Research Data |
| Language: | English |
| Published: |
Heidelberg
Universität
2023-11-13
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| 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 
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| Author Notes: | Bich-Ngoc Do, Ines Rehbein |
| Summary: | 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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| Item Description: | Produktionsdatum: 2020 Gesehen am 22.11.2023 |
| Physical Description: | Online Resource |
| DOI: | 10.11588/data/0U6IWL |