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Neural PP attachment disambiguation systems

This resource contains code for different types of neural PP attachment disambiguation systems: A disambiguation system inspired by de Kok et al. (2017) but with the ranking loss function. A disambiguation system with biaffine attention similar to the neural dependency parser in Dozat and Manning (2...

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Bibliographic Details
Main Authors: Do, Bich-Ngoc (Author) , Rehbein, Ines (Author)
Format: Database Research Data
Language:English
Published: Heidelberg Universität 2023-11-13
DOI:10.11588/data/DKWKGJ
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Online Access:Resolving-System, kostenfrei, Volltext: https://doi.org/10.11588/data/DKWKGJ
Verlag, kostenfrei, Volltext: https://heidata.uni-heidelberg.de/dataset.xhtml?persistentId=doi:10.11588/data/DKWKGJ
Verlag, kostenfrei, Volltext: https://github.com/bichngocdo/biaffine-pp-disambiguation
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Author Notes:Bich-Ngoc Do, Ines Rehbein
Description
Summary:This resource contains code for different types of neural PP attachment disambiguation systems: A disambiguation system inspired by de Kok et al. (2017) but with the ranking loss function. A disambiguation system with biaffine attention similar to the neural dependency parser in Dozat and Manning (2017). The systems are described in details in the paper: Do and Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited". We also include all pre-trained models reported in the paper.
Item Description:Produktionsdatum: 2020
Gesehen am 22.11.2023
Physical Description:Online Resource
DOI:10.11588/data/DKWKGJ

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