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• Integrated Parser

  2 resources

  Integrated parser is an application that combines and normalizes outputs of several parsers for Polish. It is based on ENIAM processing stream extended with Polish Dependency Parser, Świgra and POLFIE. Particular parsers may turned on and off according to the user requirements.

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• DG-POLFIE: POLFIE and Malt-based syntactic parser

  1 resources

  DG-POLFIE is a prototypical parser that tries to merge parse fragments generated by POLFIE using Polish Dependency Parser DG-POLFIE aims to improve the coverage of the POLFIE parser (i.e. the percentage of sentences with at least one analysis). In order to increase the number of Polish sentences and constructions that could be parsed with the POLFIE-based parser, DG-POLFIE defines some rules that use depenency structure to build full parse from the FRAGMENTS provided by POLFIE.

  Use "DG-POLFIE: POLFIE and Malt-based syntactic parser"

• UDify Pretrained Model

  3 resources

  Pretrained model weights for the UDify model, and extracted BERT weights in pytorch-transformers format. Note that these weights slightly differ from those used in the paper.

  Use "UDify Pretrained Model"

• Universal Dependencies 2.3 Models for UDPipe (2018-11-15)

  87 resources

  Tokenizer, POS Tagger, Lemmatizer and Parser models for 84 treebanks of 56 languages of Universal Depenencies 2.3 Treebanks, created solely using UD 2.3 data (http://hdl.handle.net/11234/1-2895). The model documentation including performance can be found at http://ufal.mff.cuni.cz/udpipe/models#universal_dependencies_23_models . To use these models, you need UDPipe binary version at least 1.2, which you can download from http://ufal.mff.cuni.cz/udpipe . In addition to models itself, all additional data and value of hyperparameters used for training are available in the second archive, allowing reproducible training.

  Use "Universal Dependencies 2.3 Models for UDPipe (2018-11-15)"

• Universal Dependencies 2.15 models for UDPipe 2 (2024-11-21)

  2 resources

  Tokenizer, POS Tagger, Lemmatizer and Parser models for 147 treebanks of 78 languages of Universal Depenencies 2.15 Treebanks, created solely using UD 2.15 data (https://hdl.handle.net/11234/1-5787). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_215_models . To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .

  Use "Universal Dependencies 2.15 models for UDPipe 2 (2024-11-21)"

• Universal Dependencies 2.12 models for UDPipe 2 (2023-07-17)

  2 resources

  Tokenizer, POS Tagger, Lemmatizer and Parser models for 131 treebanks of 72 languages of Universal Depenencies 2.12 Treebanks, created solely using UD 2.12 data (https://hdl.handle.net/11234/1-5150). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_212_models . To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .

  Use "Universal Dependencies 2.12 models for UDPipe 2 (2023-07-17)"

• WebLicht Dep Parsing DE

  1 resources

  WebLicht Easy Chain for Dependency Parsing (German). The pipeline makes use of WebLicht's TCF converter, the IMS tokenizer, the POS Tagger from the OpenNLP projet, and the MaltParser, a system for data-driven dependency parsing. WebLicht's Tundra can be used to visualize the result.

• WebLicht Dep Parsing EN

  1 resources

  WebLicht Easy Chain for Dependency Parsing (English). The pipeline makes use of WebLicht's TCF converter, the Stanford tokenizer, the Jitar POS Tagger, and TurboParser, a multilingual dependency parser based on linear programming relaxations. WebLicht's Tundra can be used to visualize the result.

• DARIAH DKPro-Wrapper: Depency Parsing DE

  1 resources

  The DARIAH DKPro Wrapper is a wrapper for DKPro Core, a tool for linguistic annotation.

• DARIAH DKPro-Wrapper: Depency Parsing EN

  1 resources

  The DARIAH DKPro Wrapper is a wrapper for DKPro Core, a tool for linguistic annotation.