1 to 10 of 99 Results
Nov 13, 2023 -
Real-World PP Attachment Disambiguation Dataset
Gzip Archive - 1.7 MB -
MD5: b2d04463fd249e1a19e641a99c65e70d
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Nov 13, 2023 -
Real-World PP Attachment Disambiguation Dataset
Gzip Archive - 4.3 MB -
MD5: b37e0268b451b32e52948e47baf80603
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Nov 13, 2023 -
Topological Field Labeler for German
ZIP Archive - 32.4 KB -
MD5: 3bf4fe4ba2daaade0ae9c765233145c3
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Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Do, Bich-Ngoc; Rehbein, Ines, 2023, "Topological Field Labeler for German", https://doi.org/10.11588/data/YYNQFF, heiDATA, V1
This resource contains the code of the topological labeler used in the paper: Do and Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited". For this tool, labeling topological field is formulated as a sequence labeling task. We also include in this resource two pre-... |
Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Do, Bich-Ngoc; Rehbein, Ines, 2023, "Tool for Extracting PP Attachment Disambiguation Dataset", https://doi.org/10.11588/data/RHD3KS, heiDATA, V1
This resource contains code to extract a PP attachment disambiguation dataset as described in the paper: Do and Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited". The input is in CoNLL format, and the output format is similar to the one described in de Kok et al... |
Nov 13, 2023 -
Neural Dependency Parser with Biaffine Attention
ZIP Archive - 36.0 KB -
MD5: 3e8f69e918c003c92700af524474ad31
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Nov 13, 2023 -
Neural Dependency Parser with Biaffine Attention
Gzip Archive - 361.8 MB -
MD5: c31097376ca9d2b08c013fcdbba10c6d
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Nov 13, 2023 -
Head Selection Parsers and LSTM Labelers
Gzip Archive - 47.1 MB -
MD5: 29fe91de0ec97d2282ebdac310e66e9d
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Nov 13, 2023 -
Head Selection Parsers and LSTM Labelers
Gzip Archive - 32.4 MB -
MD5: a7fa938e3000c7e0427ef3c2b3ec8d28
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Nov 13, 2023 -
Head Selection Parsers and LSTM Labelers
Gzip Archive - 32.5 MB -
MD5: 2d06256605fad989aa18b00e46922463
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