This corpus contains the text of De Latinae Linguae Reparatione authored by Marcus Antonius Sabellicus (1436–1506), annotated with respect to lemmas, part-of-speech tags, morphological features and syntactic dependencies according to the typological formalism of Universal Dependencies (UD).
POS Tagger and Lemmatizer models for EvaLatin2020 data (https://github.com/CIRCSE/LT4HALA). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#evalatin20_models .
To use these models, you need UDPipe version at least 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .
The LatinISE corpus is a text corpus collected from the LacusCurtius, Intratext and Musisque Deoque websites. Corpus texts have rich metadata containing information as genre, title, century or specific date.
This Latin corpus was built by Barbara McGillivray.
In the version 4 of the corpus the high frequency lemmas have been manually corrected and sentence boundaries have been added.
This package provides an evaluation framework, training and test data for semi-automatic recognition of sections of historical diplomatic manuscripts. The data collection consists of 57 Latin charters issued by the Royal Chancellery of 7 different types. Documents were created in the era of John the Blind, King of Bohemia (1310–1346) and Count of Luxembourg. Manuscripts were digitized, transcribed, and typical sections of medieval charters ('corroboratio', 'datatio', 'dispositio', 'inscriptio', 'intitulatio', 'narratio', and 'publicatio') were manually tagged. Manuscripts also contain additional metadata, such as manually marked named entities and short Czech abstracts.
Recognition models are first trained using manually marked sections in training documents and the trained model can then be used for recognition of the sections in the test data. The parsing script supports methods based on Cosine Distance, TF-IDF weighting and adapted Viterbi algorithm.
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.
Tokenizer, POS Tagger, Lemmatizer and Parser models for 99 treebanks of 63 languages of Universal Depenencies 2.6 Treebanks, created solely using UD 2.6 data (https://hdl.handle.net/11234/1-3226). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_26_models .
To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .