Texts in 107 languages from the W2C corpus (http://hdl.handle.net/11858/00-097C-0000-0022-6133-9), first 1,000,000 tokens per language, tagged by the delexicalized tagger described in Yu et al. (2016, LREC, Portorož, Slovenia).
Changes in version 1.1:
1. Universal Dependencies tagset instead of the older and smaller Google Universal POS tagset.
2. SVM classifier trained on Universal Dependencies 1.2 instead of HamleDT 2.0.
3. Balto-Slavic languages, Germanic languages and Romance languages were tagged by classifier trained only on the respective group of languages. Other languages were tagged by a classifier trained on all available languages. The "c7" combination from version 1.0 is no longer used.
This package contains an extended version of the test collection used in the CLEF eHealth Information Retrieval tasks in 2013--2015. Compared to the original version, it provides complete query translations into Czech, French, German, Hungarian, Polish, Spanish and Swedish and additional relevance assessment.
This package contains data sets for development and testing of machine translation of medical queries between Czech, English, French, German, Hungarian, Polish, Spanish ans Swedish. The queries come from general public and medical experts. This is version 2.0 extending the previous version by adding Hungarian, Polish, Spanish, and Swedish translations.
This package contains data sets for development (Section dev) and testing (Section test) of machine translation of sentences from summaries of medical articles between Czech, English, French, German, Hungarian, Polish, Spanish
and Swedish. Version 2.0 extends the previous version by adding Hungarian, Polish, Spanish, and Swedish translations.
Wikipedia plain text data obtained from Wikipedia dumps with WikiExtractor in February 2018.
The data come from all Wikipedias for which dumps could be downloaded at [https://dumps.wikimedia.org/]. This amounts to 297 Wikipedias, usually corresponding to individual languages and identified by their ISO codes. Several special Wikipedias are included, most notably "simple" (Simple English Wikipedia) and "incubator" (tiny hatching Wikipedias in various languages).
For a list of all the Wikipedias, see [https://meta.wikimedia.org/wiki/List_of_Wikipedias].
The script which can be used to get new version of the data is included, but note that Wikipedia limits the download speed for downloading a lot of the dumps, so it takes a few days to download all of them (but one or a few can be downloaded fast).
Also, the format of the dumps changes time to time, so the script will probably eventually stop working one day.
The WikiExtractor tool [http://medialab.di.unipi.it/wiki/Wikipedia_Extractor] used to extract text from the Wikipedia dumps is not mine, I only modified it slightly to produce plaintext outputs [https://github.com/ptakopysk/wikiextractor].
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.
Tokenizer, POS Tagger, Lemmatizer and Parser models for 123 treebanks of 69 languages of Universal Depenencies 2.10 Treebanks, created solely using UD 2.10 data (https://hdl.handle.net/11234/1-4758). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_210_models .
To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .
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 .
Tokenizer, POS Tagger, Lemmatizer and Parser models for 90 treebanks of 60 languages of Universal Depenencies 2.4 Treebanks, created solely using UD 2.4 data (http://hdl.handle.net/11234/1-2988). The model documentation including performance can be found at http://ufal.mff.cuni.cz/udpipe/models#universal_dependencies_24_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.
Tokenizer, POS Tagger, Lemmatizer and Parser models for 94 treebanks of 61 languages of Universal Depenencies 2.5 Treebanks, created solely using UD 2.5 data (http://hdl.handle.net/11234/1-3105). The model documentation including performance can be found at http://ufal.mff.cuni.cz/udpipe/models#universal_dependencies_25_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.