Like any supervised machine-learning tool, UDPipe needs a trained linguistic model. This section describes the available models.

1. Universal Dependencies 2.5 Models

Universal Dependencies 2.5 Models are distributed under the CC BY-NC-SA licence. The models are based solely on Universal Dependencies 2.5 treebanks. The models work in UDPipe version 1.2 and later.

Universal Dependencies 2.5 Models are versioned according to the date released in the format YYMMDD, where YY, MM and DD are two-digit representation of year, month and day, respectively. The latest version is 191206.

1.1. Download

The latest version 190531 of the Universal Dependencies 2.5 models can be downloaded from LINDAT/CLARIN repository.

1.2. Acknowledgements

This work has been partially supported and has been using language resources and tools developed, stored and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).

The models were trained on Universal Dependencies 2.5 treebanks.

For the UD treebanks which do not contain original plain text version, raw text is used to train the tokenizer instead. The plain texts were taken from the W2C – Web to Corpus.

1.2.1. Publications

• (Straka et al. 2017) Milan Straka and Jana Straková. Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe. In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, Vancouver, Canada, August 2017.
• (Straka et al. 2016) Straka Milan, Hajič Jan, Straková Jana. UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), Portorož, Slovenia, May 2016.

1.3. Model Description

The Universal Dependencies 2.5 models contain 94 models of 61 languages, each consisting of a tokenizer, tagger, lemmatizer and dependency parser, all trained using the UD data. We used the original train-dev-test split, but for treebanks with only train and no dev data we used last 10% of the train data as dev data. We produce models only for treebanks with at least 1000 training words.

The tokenizer is trained using the SpaceAfter=No features. If the features are not present in the data, they can be filled in using raw text in the language in question.

The tagger, lemmatizer and parser are trained using gold UD data.

Details about model architecture and training process can be found in the (Straka et al. 2017) paper.

1.3.1. Reproducible Training

In case you want to train the same models, scripts for downloading and resplitting UD 2.5 data, precomputed word embedding, raw texts for tokenizers, all hyperparameter values and training scripts are available in the second archive on the model download page.

1.4. Model Performance

We present the tagger, lemmatizer and parser performance, measured on the testing portion of the data, evaluated in three different settings: using raw text only, using gold tokenization only, and using gold tokenization plus gold morphology (UPOS, XPOS, FEATS and Lemma).

Treebank	Mode	Words	Sents	UPOS	XPOS	UFeats	AllTags	Lemma	UAS	LAS	MLAS	BLEX
Afrikaans-AfriBooms	Raw text	99.6%	98.2%	95.0%	90.6%	94.6%	90.6%	96.5%	81.6%	77.6%	64.4%	66.5%
Afrikaans-AfriBooms	Gold tok	-	-	95.3%	90.8%	94.9%	90.8%	96.7%	82.5%	78.4%	65.1%	67.2%
Afrikaans-AfriBooms	Gold tok+mor	-	-	-	-	-	-	-	87.6%	85.0%	77.0%	79.6%
Ancient Greek-Perseus	Raw text	100.0%	98.8%	82.2%	72.2%	85.7%	72.2%	82.7%	64.0%	57.0%	30.2%	38.2%
Ancient Greek-Perseus	Gold tok	-	-	82.2%	72.2%	85.7%	72.2%	82.7%	64.1%	57.2%	30.3%	38.4%
Ancient Greek-Perseus	Gold tok+mor	-	-	-	-	-	-	-	68.7%	63.9%	53.1%	57.2%
Ancient Greek-PROIEL	Raw text	100.0%	48.0%	96.0%	96.2%	88.6%	87.2%	93.2%	72.2%	67.6%	49.9%	56.0%
Ancient Greek-PROIEL	Gold tok	-	-	96.1%	96.3%	88.7%	87.4%	93.2%	77.0%	72.1%	54.4%	60.3%
Ancient Greek-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	80.2%	76.4%	66.7%	70.3%
Arabic-PADT	Raw text	94.6%	82.1%	90.4%	84.0%	84.2%	83.8%	88.5%	72.7%	68.1%	56.2%	59.2%
Arabic-PADT	Gold tok	-	-	95.6%	89.0%	89.2%	88.8%	92.9%	82.0%	76.8%	63.6%	66.3%
Arabic-PADT	Gold tok+mor	-	-	-	-	-	-	-	83.9%	80.7%	75.7%	76.8%
Armenian-ArmTDP	Raw text	99.3%	97.8%	92.0%	-	84.7%	83.4%	91.8%	75.6%	68.5%	51.2%	57.4%
Armenian-ArmTDP	Gold tok	-	-	92.5%	-	85.2%	83.8%	92.4%	76.9%	69.7%	51.5%	57.9%
Armenian-ArmTDP	Gold tok+mor	-	-	-	-	-	-	-	82.4%	77.2%	70.9%	71.9%
Basque-BDT	Raw text	99.9%	99.8%	92.3%	-	87.3%	84.8%	93.5%	75.0%	69.9%	57.4%	63.2%
Basque-BDT	Gold tok	-	-	92.4%	-	87.4%	84.8%	93.6%	75.1%	70.0%	57.4%	63.2%
Basque-BDT	Gold tok+mor	-	-	-	-	-	-	-	82.1%	78.4%	75.2%	77.2%
Belarusian-HSE	Raw text	99.8%	78.7%	84.3%	32.0%	65.3%	23.9%	75.0%	58.6%	52.9%	28.8%	33.1%
Belarusian-HSE	Gold tok	-	-	84.4%	32.1%	65.4%	24.1%	75.2%	59.5%	53.8%	29.3%	33.8%
Belarusian-HSE	Gold tok+mor	-	-	-	-	-	-	-	72.9%	69.6%	62.4%	63.3%
Bulgarian-BTB	Raw text	99.9%	94.2%	97.6%	94.3%	95.4%	93.8%	94.6%	89.1%	85.1%	75.4%	74.0%
Bulgarian-BTB	Gold tok	-	-	97.8%	94.5%	95.5%	93.9%	94.7%	90.0%	85.9%	76.1%	74.7%
Bulgarian-BTB	Gold tok+mor	-	-	-	-	-	-	-	92.5%	89.1%	84.4%	84.7%
Catalan-AnCora	Raw text	100.0%	99.4%	98.1%	98.0%	97.7%	96.9%	98.2%	89.0%	85.9%	77.3%	77.8%
Catalan-AnCora	Gold tok	-	-	98.1%	98.0%	97.7%	97.0%	98.2%	89.1%	86.0%	77.4%	77.8%
Catalan-AnCora	Gold tok+mor	-	-	-	-	-	-	-	91.0%	88.5%	82.5%	83.0%
Chinese-GSD	Raw text	90.3%	99.1%	84.1%	84.0%	89.0%	82.8%	90.3%	61.6%	57.8%	50.8%	54.7%
Chinese-GSD	Gold tok	-	-	92.2%	92.0%	98.7%	90.8%	100.0%	74.4%	69.5%	62.2%	67.8%
Chinese-GSD	Gold tok+mor	-	-	-	-	-	-	-	82.6%	80.5%	77.5%	79.6%
Chinese-GSDSimp	Raw text	90.3%	99.1%	84.2%	84.1%	89.0%	82.8%	90.3%	62.6%	58.7%	51.3%	55.2%
Chinese-GSDSimp	Gold tok	-	-	92.0%	91.8%	98.6%	90.5%	100.0%	74.1%	69.0%	61.8%	67.1%
Chinese-GSDSimp	Gold tok+mor	-	-	-	-	-	-	-	82.7%	80.4%	77.5%	79.6%
Classical Chinese-Kyoto	Raw text	99.5%	41.7%	89.9%	89.2%	92.3%	86.7%	99.5%	68.9%	62.9%	59.1%	61.3%
Classical Chinese-Kyoto	Gold tok	-	-	92.0%	91.3%	93.6%	89.2%	100.0%	81.0%	74.7%	71.0%	73.5%
Classical Chinese-Kyoto	Gold tok+mor	-	-	-	-	-	-	-	90.0%	85.9%	84.6%	85.0%
Coptic-Scriptorium	Raw text	70.7%	27.7%	67.1%	64.6%	50.2%	46.3%	68.7%	43.8%	41.8%	12.7%	32.0%
Coptic-Scriptorium	Gold tok	-	-	94.0%	88.5%	70.6%	62.4%	96.0%	85.3%	80.4%	29.9%	69.8%
Coptic-Scriptorium	Gold tok+mor	-	-	-	-	-	-	-	88.9%	85.7%	75.8%	78.1%
Croatian-SET	Raw text	100.0%	94.4%	96.5%	90.3%	90.9%	89.9%	95.3%	83.7%	77.7%	64.8%	69.3%
Croatian-SET	Gold tok	-	-	96.5%	90.4%	91.1%	90.1%	95.3%	84.2%	78.1%	65.3%	69.7%
Croatian-SET	Gold tok+mor	-	-	-	-	-	-	-	86.8%	82.2%	77.2%	78.9%
Czech-CAC	Raw text	100.0%	99.7%	98.3%	91.0%	90.0%	89.6%	97.0%	86.3%	82.8%	70.5%	77.0%
Czech-CAC	Gold tok	-	-	98.3%	91.0%	90.0%	89.6%	97.0%	86.4%	82.9%	70.5%	77.1%
Czech-CAC	Gold tok+mor	-	-	-	-	-	-	-	89.7%	87.3%	84.2%	85.0%
Czech-CLTT	Raw text	99.7%	97.4%	97.3%	87.3%	87.4%	87.1%	96.1%	78.9%	75.4%	60.0%	68.9%
Czech-CLTT	Gold tok	-	-	97.6%	87.5%	87.7%	87.4%	96.4%	79.6%	76.1%	60.4%	69.4%
Czech-CLTT	Gold tok+mor	-	-	-	-	-	-	-	82.7%	79.6%	74.7%	75.3%
Czech-FicTree	Raw text	100.0%	99.0%	97.1%	89.9%	90.8%	89.4%	97.1%	86.3%	82.0%	68.7%	74.3%
Czech-FicTree	Gold tok	-	-	97.1%	90.0%	90.8%	89.5%	97.1%	86.4%	82.1%	68.8%	74.4%
Czech-FicTree	Gold tok+mor	-	-	-	-	-	-	-	90.5%	87.7%	83.3%	84.1%
Czech-PDT	Raw text	99.9%	93.3%	98.2%	92.7%	92.4%	91.9%	97.8%	87.0%	84.0%	74.4%	79.4%
Czech-PDT	Gold tok	-	-	98.3%	92.9%	92.5%	92.0%	97.9%	87.8%	84.7%	75.0%	80.0%
Czech-PDT	Gold tok+mor	-	-	-	-	-	-	-	90.3%	88.2%	85.6%	86.1%
Danish-DDT	Raw text	99.8%	89.8%	95.4%	-	94.8%	93.4%	94.7%	79.3%	76.0%	66.4%	66.8%
Danish-DDT	Gold tok	-	-	95.6%	-	95.0%	93.6%	94.9%	80.2%	76.8%	67.2%	67.5%
Danish-DDT	Gold tok+mor	-	-	-	-	-	-	-	84.8%	82.4%	77.4%	79.1%
Dutch-Alpino	Raw text	99.8%	88.6%	94.1%	91.5%	93.3%	90.7%	95.1%	82.4%	78.2%	62.3%	65.1%
Dutch-Alpino	Gold tok	-	-	94.3%	91.7%	93.5%	90.9%	95.3%	83.3%	79.0%	63.3%	66.1%
Dutch-Alpino	Gold tok+mor	-	-	-	-	-	-	-	86.9%	83.2%	74.8%	76.1%
Dutch-LassySmall	Raw text	99.8%	75.4%	94.1%	91.8%	93.7%	91.0%	95.5%	79.0%	75.0%	62.6%	63.2%
Dutch-LassySmall	Gold tok	-	-	94.2%	92.1%	94.2%	91.3%	95.7%	82.4%	78.0%	66.3%	67.0%
Dutch-LassySmall	Gold tok+mor	-	-	-	-	-	-	-	87.6%	84.5%	78.6%	79.3%
English-EWT	Raw text	98.9%	77.4%	93.3%	92.8%	94.2%	91.3%	95.5%	80.2%	77.0%	67.7%	69.5%
English-EWT	Gold tok	-	-	94.4%	93.9%	95.4%	92.5%	96.4%	84.4%	81.1%	71.6%	73.6%
English-EWT	Gold tok+mor	-	-	-	-	-	-	-	88.1%	86.2%	82.4%	83.1%
English-GUM	Raw text	99.7%	82.3%	93.8%	93.3%	94.3%	92.2%	94.9%	80.2%	76.2%	64.8%	65.1%
English-GUM	Gold tok	-	-	94.1%	93.7%	94.6%	92.5%	95.2%	82.0%	77.9%	66.2%	66.6%
English-GUM	Gold tok+mor	-	-	-	-	-	-	-	86.5%	84.4%	78.0%	79.0%
English-LinES	Raw text	99.9%	87.5%	94.9%	92.7%	94.9%	90.3%	97.1%	80.4%	75.9%	67.0%	69.5%
English-LinES	Gold tok	-	-	95.0%	92.8%	95.0%	90.4%	97.1%	81.2%	76.6%	67.7%	70.2%
English-LinES	Gold tok+mor	-	-	-	-	-	-	-	85.5%	82.3%	78.1%	79.8%
English-ParTUT	Raw text	99.7%	100.0%	93.6%	93.2%	93.4%	91.7%	96.7%	83.9%	80.4%	69.0%	71.4%
English-ParTUT	Gold tok	-	-	93.8%	93.5%	93.6%	91.9%	97.0%	84.2%	80.6%	69.1%	71.5%
English-ParTUT	Gold tok+mor	-	-	-	-	-	-	-	86.8%	85.4%	79.0%	80.1%
Estonian-EDT	Raw text	100.0%	91.6%	95.6%	96.8%	93.4%	91.8%	90.6%	79.5%	75.8%	68.3%	64.7%
Estonian-EDT	Gold tok	-	-	95.7%	96.8%	93.5%	91.8%	90.6%	80.3%	76.5%	69.0%	65.3%
Estonian-EDT	Gold tok+mor	-	-	-	-	-	-	-	85.5%	83.3%	80.4%	81.5%
Estonian-EWT	Raw text	99.1%	67.0%	83.2%	85.6%	79.5%	76.2%	79.8%	60.1%	51.2%	38.8%	36.7%
Estonian-EWT	Gold tok	-	-	84.0%	86.3%	80.2%	77.0%	80.4%	62.6%	53.2%	39.8%	37.6%
Estonian-EWT	Gold tok+mor	-	-	-	-	-	-	-	74.1%	69.9%	64.6%	65.7%
Finnish-FTB	Raw text	99.9%	86.8%	91.5%	90.8%	92.5%	88.9%	88.5%	79.4%	74.9%	64.1%	60.9%
Finnish-FTB	Gold tok	-	-	91.8%	91.0%	92.7%	89.2%	88.6%	81.1%	76.6%	65.9%	62.6%
Finnish-FTB	Gold tok+mor	-	-	-	-	-	-	-	89.9%	87.6%	82.9%	84.2%
Finnish-TDT	Raw text	99.7%	88.6%	94.3%	95.4%	92.0%	90.8%	86.9%	80.5%	76.8%	68.6%	62.8%
Finnish-TDT	Gold tok	-	-	94.7%	95.8%	92.4%	91.2%	87.2%	81.8%	78.1%	69.5%	63.6%
Finnish-TDT	Gold tok+mor	-	-	-	-	-	-	-	86.8%	84.7%	81.6%	82.5%
French-GSD	Raw text	98.8%	93.6%	95.8%	-	95.5%	94.5%	96.6%	87.1%	84.3%	74.4%	76.3%
French-GSD	Gold tok	-	-	97.1%	-	96.6%	95.6%	97.8%	89.0%	86.3%	76.0%	77.7%
French-GSD	Gold tok+mor	-	-	-	-	-	-	-	91.1%	89.2%	83.9%	84.2%
French-ParTUT	Raw text	99.4%	100.0%	94.6%	94.2%	91.9%	90.6%	95.0%	87.4%	83.5%	66.4%	71.5%
French-ParTUT	Gold tok	-	-	95.3%	94.8%	92.6%	91.3%	95.6%	88.0%	84.3%	67.4%	72.0%
French-ParTUT	Gold tok+mor	-	-	-	-	-	-	-	91.0%	89.0%	82.1%	83.4%
French-Sequoia	Raw text	99.1%	87.5%	96.1%	-	95.0%	94.1%	96.9%	84.8%	82.1%	72.5%	75.1%
French-Sequoia	Gold tok	-	-	97.1%	-	95.9%	95.0%	97.8%	86.8%	84.1%	74.5%	76.8%
French-Sequoia	Gold tok+mor	-	-	-	-	-	-	-	89.7%	88.1%	83.8%	84.0%
French-Spoken	Raw text	99.1%	21.1%	91.9%	96.3%	-	89.6%	94.5%	69.2%	63.3%	51.6%	51.8%
French-Spoken	Gold tok	-	-	93.1%	97.2%	-	90.6%	95.5%	76.1%	69.9%	59.4%	59.4%
French-Spoken	Gold tok+mor	-	-	-	-	-	-	-	80.7%	76.5%	67.5%	68.6%
Galician-CTG	Raw text	99.2%	97.2%	96.3%	95.8%	99.0%	95.4%	96.2%	79.3%	76.2%	62.5%	65.4%
Galician-CTG	Gold tok	-	-	97.0%	96.5%	99.8%	96.2%	96.9%	80.8%	77.7%	64.3%	67.2%
Galician-CTG	Gold tok+mor	-	-	-	-	-	-	-	83.0%	80.7%	69.4%	74.1%
Galician-TreeGal	Raw text	98.7%	88.0%	91.1%	87.3%	89.5%	86.6%	92.5%	72.1%	66.6%	49.8%	52.2%
Galician-TreeGal	Gold tok	-	-	92.2%	88.1%	90.4%	87.4%	93.6%	75.1%	69.1%	52.4%	55.2%
Galician-TreeGal	Gold tok+mor	-	-	-	-	-	-	-	81.7%	77.5%	69.4%	70.7%
German-GSD	Raw text	99.6%	80.9%	91.7%	79.5%	69.8%	62.9%	95.4%	78.1%	72.7%	34.5%	61.4%
German-GSD	Gold tok	-	-	92.1%	79.8%	70.2%	63.4%	95.8%	80.6%	75.0%	35.9%	63.6%
German-GSD	Gold tok+mor	-	-	-	-	-	-	-	85.5%	81.2%	72.5%	75.3%
German-HDT	Raw text	99.9%	92.6%	97.8%	97.4%	91.4%	91.0%	94.5%	94.0%	92.3%	77.0%	81.4%
German-HDT	Gold tok	-	-	97.9%	97.5%	91.5%	91.1%	94.6%	94.6%	92.9%	77.5%	82.0%
German-HDT	Gold tok+mor	-	-	-	-	-	-	-	95.5%	94.4%	91.5%	91.7%
Gothic-PROIEL	Raw text	100.0%	31.1%	94.3%	94.8%	87.4%	85.5%	92.6%	68.6%	62.0%	48.8%	54.6%
Gothic-PROIEL	Gold tok	-	-	94.8%	95.2%	87.6%	85.9%	92.7%	76.8%	70.0%	56.2%	61.7%
Gothic-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	80.0%	76.0%	69.1%	72.5%
Greek-GDT	Raw text	99.9%	90.2%	95.7%	95.7%	90.3%	89.0%	94.6%	86.5%	83.0%	66.2%	69.6%
Greek-GDT	Gold tok	-	-	95.9%	95.9%	90.5%	89.2%	94.7%	87.2%	83.7%	66.8%	70.2%
Greek-GDT	Gold tok+mor	-	-	-	-	-	-	-	89.7%	87.9%	81.6%	82.7%
Hebrew-HTB	Raw text	85.0%	99.4%	80.5%	80.5%	78.7%	77.7%	81.6%	61.7%	58.3%	44.6%	47.5%
Hebrew-HTB	Gold tok	-	-	94.9%	94.9%	92.7%	91.5%	95.4%	83.6%	79.6%	64.3%	67.1%
Hebrew-HTB	Gold tok+mor	-	-	-	-	-	-	-	87.0%	84.9%	78.4%	78.8%
Hindi-HDTB	Raw text	100.0%	98.9%	95.9%	94.9%	90.4%	87.8%	98.1%	91.3%	87.2%	69.2%	80.1%
Hindi-HDTB	Gold tok	-	-	95.9%	95.0%	90.4%	87.8%	98.1%	91.3%	87.2%	69.3%	80.2%
Hindi-HDTB	Gold tok+mor	-	-	-	-	-	-	-	93.8%	90.8%	85.4%	86.6%
Hungarian-Szeged	Raw text	99.8%	95.9%	90.6%	-	88.1%	86.4%	88.5%	72.8%	67.2%	53.7%	57.9%
Hungarian-Szeged	Gold tok	-	-	90.7%	-	88.2%	86.5%	88.7%	73.3%	67.6%	53.9%	58.1%
Hungarian-Szeged	Gold tok+mor	-	-	-	-	-	-	-	80.5%	77.6%	72.7%	76.6%
Indonesian-GSD	Raw text	100.0%	94.1%	93.0%	92.2%	93.9%	87.1%	92.2%	81.0%	74.6%	63.6%	62.9%
Indonesian-GSD	Gold tok	-	-	93.0%	92.2%	93.9%	87.1%	92.2%	81.2%	74.8%	63.9%	63.2%
Indonesian-GSD	Gold tok+mor	-	-	-	-	-	-	-	84.0%	79.8%	76.4%	78.3%
Irish-IDT	Raw text	99.7%	97.5%	90.0%	88.9%	77.7%	74.5%	87.9%	76.8%	66.4%	39.4%	47.9%
Irish-IDT	Gold tok	-	-	90.2%	89.2%	78.0%	74.7%	88.2%	77.1%	66.8%	39.5%	48.1%
Irish-IDT	Gold tok+mor	-	-	-	-	-	-	-	80.9%	73.9%	62.7%	64.9%
Italian-ISDT	Raw text	99.8%	98.8%	97.2%	97.0%	97.1%	96.2%	97.4%	88.8%	86.2%	76.8%	76.7%
Italian-ISDT	Gold tok	-	-	97.3%	97.2%	97.2%	96.3%	97.5%	89.1%	86.6%	77.3%	77.2%
Italian-ISDT	Gold tok+mor	-	-	-	-	-	-	-	91.3%	89.7%	84.2%	84.5%
Italian-ParTUT	Raw text	99.7%	100.0%	97.0%	96.4%	96.3%	95.2%	96.5%	87.5%	84.3%	73.2%	72.4%
Italian-ParTUT	Gold tok	-	-	97.1%	96.6%	96.5%	95.3%	96.7%	87.4%	84.3%	73.1%	72.3%
Italian-ParTUT	Gold tok+mor	-	-	-	-	-	-	-	89.7%	87.6%	79.8%	80.7%
Italian-PoSTWITA	Raw text	99.5%	30.5%	94.0%	93.7%	94.4%	92.4%	95.1%	74.4%	69.4%	56.8%	57.4%
Italian-PoSTWITA	Gold tok	-	-	94.6%	94.2%	94.9%	92.9%	95.6%	80.1%	74.8%	63.8%	64.6%
Italian-PoSTWITA	Gold tok+mor	-	-	-	-	-	-	-	84.4%	80.0%	73.7%	74.3%
Italian-TWITTIRO	Raw text	99.1%	36.8%	90.4%	89.7%	89.8%	86.9%	90.2%	71.9%	65.3%	47.8%	48.1%
Italian-TWITTIRO	Gold tok	-	-	91.5%	90.7%	91.0%	87.9%	91.5%	76.3%	69.4%	52.1%	52.8%
Italian-TWITTIRO	Gold tok+mor	-	-	-	-	-	-	-	84.1%	78.7%	69.9%	70.8%
Italian-VIT	Raw text	99.7%	94.7%	96.1%	95.0%	95.9%	93.5%	96.8%	83.5%	79.4%	67.2%	68.5%
Italian-VIT	Gold tok	-	-	96.4%	95.3%	96.1%	93.8%	97.0%	84.2%	80.1%	67.9%	69.2%
Italian-VIT	Gold tok+mor	-	-	-	-	-	-	-	87.3%	84.4%	77.4%	78.3%
Japanese-GSD	Raw text	90.6%	94.7%	88.0%	87.7%	90.6%	87.7%	89.8%	75.2%	73.7%	60.6%	62.6%
Japanese-GSD	Gold tok	-	-	96.9%	96.4%	100.0%	96.4%	99.1%	92.7%	90.7%	80.6%	82.8%
Japanese-GSD	Gold tok+mor	-	-	-	-	-	-	-	94.8%	93.8%	87.0%	87.1%
Korean-GSD	Raw text	99.9%	93.9%	93.6%	81.7%	99.6%	79.5%	87.1%	69.6%	61.5%	54.1%	50.8%
Korean-GSD	Gold tok	-	-	93.7%	81.9%	99.7%	79.7%	87.2%	70.3%	62.1%	54.8%	51.4%
Korean-GSD	Gold tok+mor	-	-	-	-	-	-	-	72.5%	65.5%	60.4%	61.6%
Korean-Kaist	Raw text	100.0%	100.0%	93.3%	80.1%	-	80.1%	88.5%	77.9%	70.6%	61.9%	58.1%
Korean-Kaist	Gold tok	-	-	93.4%	80.1%	-	80.1%	88.5%	78.0%	70.7%	62.0%	58.1%
Korean-Kaist	Gold tok+mor	-	-	-	-	-	-	-	80.3%	73.7%	67.8%	68.4%
Latin-ITTB	Raw text	100.0%	92.4%	97.1%	93.0%	93.4%	91.4%	98.0%	83.4%	80.1%	70.6%	75.5%
Latin-ITTB	Gold tok	-	-	97.1%	93.0%	93.3%	91.4%	98.0%	83.9%	80.5%	70.7%	75.5%
Latin-ITTB	Gold tok+mor	-	-	-	-	-	-	-	87.8%	85.8%	81.9%	83.0%
Latin-PROIEL	Raw text	99.9%	36.8%	94.5%	94.7%	86.7%	85.6%	94.5%	65.9%	60.1%	47.7%	54.4%
Latin-PROIEL	Gold tok	-	-	94.7%	94.8%	87.2%	86.2%	94.7%	73.4%	67.3%	54.9%	61.3%
Latin-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	77.2%	73.4%	67.1%	70.3%
Latin-Perseus	Raw text	100.0%	98.5%	83.3%	67.2%	72.1%	67.2%	78.0%	57.7%	47.1%	29.4%	31.9%
Latin-Perseus	Gold tok	-	-	83.3%	67.2%	72.1%	67.2%	77.9%	57.9%	47.2%	29.4%	31.9%
Latin-Perseus	Gold tok+mor	-	-	-	-	-	-	-	67.6%	61.8%	55.9%	59.1%
Latvian-LVTB	Raw text	99.3%	98.7%	93.5%	84.3%	89.5%	83.9%	92.7%	78.8%	74.2%	62.1%	65.7%
Latvian-LVTB	Gold tok	-	-	94.0%	84.8%	90.1%	84.5%	93.3%	79.7%	75.1%	62.9%	66.5%
Latvian-LVTB	Gold tok+mor	-	-	-	-	-	-	-	86.4%	83.5%	79.8%	81.0%
Lithuanian-ALKSNIS	Raw text	99.9%	87.9%	90.4%	80.7%	82.3%	80.4%	88.8%	69.0%	62.5%	48.8%	52.0%
Lithuanian-ALKSNIS	Gold tok	-	-	90.5%	80.9%	82.5%	80.6%	88.9%	69.8%	63.4%	49.4%	52.5%
Lithuanian-ALKSNIS	Gold tok+mor	-	-	-	-	-	-	-	77.2%	73.9%	70.6%	71.6%
Lithuanian-HSE	Raw text	97.3%	97.3%	73.2%	72.1%	68.2%	62.7%	71.1%	46.9%	33.5%	21.6%	22.1%
Lithuanian-HSE	Gold tok	-	-	74.1%	73.1%	69.2%	63.6%	72.0%	48.3%	34.7%	21.9%	22.3%
Lithuanian-HSE	Gold tok+mor	-	-	-	-	-	-	-	56.9%	48.1%	42.6%	44.4%
Maltese-MUDT	Raw text	99.8%	86.3%	93.8%	93.5%	-	93.2%	-	77.7%	71.8%	58.4%	61.9%
Maltese-MUDT	Gold tok	-	-	93.9%	93.7%	-	93.4%	-	78.0%	72.2%	58.6%	62.1%
Maltese-MUDT	Gold tok+mor	-	-	-	-	-	-	-	82.2%	77.9%	68.4%	69.7%
Marathi-UFAL	Raw text	90.2%	92.6%	71.5%	-	60.8%	58.2%	76.2%	60.5%	49.5%	23.9%	30.7%
Marathi-UFAL	Gold tok	-	-	77.7%	-	63.4%	60.4%	76.5%	68.5%	54.9%	26.0%	31.0%
Marathi-UFAL	Gold tok+mor	-	-	-	-	-	-	-	77.9%	67.7%	60.7%	63.1%
North Sami-Giella	Raw text	99.9%	98.8%	87.8%	89.4%	82.5%	78.4%	82.0%	64.7%	57.9%	46.7%	43.2%
North Sami-Giella	Gold tok	-	-	87.9%	89.6%	82.6%	78.5%	82.1%	64.9%	58.2%	46.9%	43.5%
North Sami-Giella	Gold tok+mor	-	-	-	-	-	-	-	81.4%	78.7%	74.2%	77.2%
Norwegian-Bokmaal	Raw text	100.0%	96.5%	96.6%	-	95.4%	94.1%	96.9%	87.2%	84.4%	75.3%	77.1%
Norwegian-Bokmaal	Gold tok	-	-	96.7%	-	95.4%	94.2%	97.0%	87.5%	84.7%	75.6%	77.5%
Norwegian-Bokmaal	Gold tok+mor	-	-	-	-	-	-	-	92.0%	90.2%	86.1%	86.9%
Norwegian-Nynorsk	Raw text	99.9%	94.1%	96.0%	-	94.9%	93.6%	96.3%	85.7%	82.8%	72.8%	74.5%
Norwegian-Nynorsk	Gold tok	-	-	96.2%	-	95.0%	93.7%	96.4%	86.4%	83.5%	73.6%	75.2%
Norwegian-Nynorsk	Gold tok+mor	-	-	-	-	-	-	-	91.1%	89.2%	84.7%	85.8%
Norwegian-NynorskLIA	Raw text	99.8%	99.5%	93.7%	-	93.2%	90.4%	96.2%	74.2%	68.9%	55.9%	60.1%
Norwegian-NynorskLIA	Gold tok	-	-	93.8%	-	93.3%	90.5%	96.4%	74.4%	69.1%	56.0%	60.3%
Norwegian-NynorskLIA	Gold tok+mor	-	-	-	-	-	-	-	81.1%	76.8%	69.1%	71.3%
Old Church Slavonic-PROIEL	Raw text	100.0%	41.4%	93.5%	93.7%	86.8%	85.5%	90.9%	71.2%	65.3%	54.8%	59.5%
Old Church Slavonic-PROIEL	Gold tok	-	-	93.8%	94.0%	87.4%	86.2%	91.0%	79.5%	73.2%	62.4%	66.0%
Old Church Slavonic-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	85.1%	81.3%	76.8%	79.6%
Old French-SRCMF	Raw text	99.9%	100.0%	94.2%	93.8%	96.0%	93.3%	-	85.5%	79.3%	70.9%	74.6%
Old French-SRCMF	Gold tok	-	-	94.3%	93.9%	96.1%	93.4%	-	85.6%	79.4%	71.0%	74.7%
Old French-SRCMF	Gold tok+mor	-	-	-	-	-	-	-	88.8%	84.4%	78.4%	79.7%
Old Russian-TOROT	Raw text	100.0%	29.6%	89.9%	90.0%	81.8%	79.6%	81.2%	63.9%	56.9%	42.9%	44.2%
Old Russian-TOROT	Gold tok	-	-	90.5%	90.5%	82.5%	80.5%	81.3%	73.4%	65.9%	51.5%	50.8%
Old Russian-TOROT	Gold tok+mor	-	-	-	-	-	-	-	80.5%	76.4%	70.4%	73.2%
Persian-Seraji	Raw text	99.7%	98.8%	96.0%	95.9%	96.1%	95.4%	93.6%	83.6%	79.6%	72.8%	70.1%
Persian-Seraji	Gold tok	-	-	96.3%	96.3%	96.4%	95.7%	93.9%	84.3%	80.2%	73.3%	70.5%
Persian-Seraji	Gold tok+mor	-	-	-	-	-	-	-	87.2%	84.3%	80.0%	80.8%
Polish-LFG	Raw text	99.8%	99.7%	96.7%	87.2%	89.1%	86.5%	94.5%	90.9%	87.4%	74.4%	78.5%
Polish-LFG	Gold tok	-	-	96.9%	87.3%	89.2%	86.7%	94.6%	91.3%	87.8%	74.7%	78.8%
Polish-LFG	Gold tok+mor	-	-	-	-	-	-	-	96.2%	94.8%	92.9%	93.1%
Polish-PDB	Raw text	99.8%	97.3%	97.1%	88.1%	88.6%	87.5%	96.0%	86.5%	82.7%	68.8%	75.4%
Polish-PDB	Gold tok	-	-	97.2%	88.2%	88.8%	87.7%	96.1%	87.0%	83.2%	69.1%	75.8%
Polish-PDB	Gold tok+mor	-	-	-	-	-	-	-	90.5%	88.8%	86.0%	86.3%
Portuguese-Bosque	Raw text	99.5%	87.8%	95.9%	-	94.5%	92.7%	96.7%	85.9%	81.9%	68.0%	71.8%
Portuguese-Bosque	Gold tok	-	-	96.4%	-	95.0%	93.2%	97.2%	87.2%	83.1%	69.0%	73.0%
Portuguese-Bosque	Gold tok+mor	-	-	-	-	-	-	-	89.3%	86.3%	79.5%	80.5%
Portuguese-GSD	Raw text	99.8%	97.1%	97.0%	97.0%	99.7%	97.0%	98.5%	88.0%	85.9%	77.8%	78.5%
Portuguese-GSD	Gold tok	-	-	97.2%	97.2%	99.9%	97.2%	98.7%	88.4%	86.3%	78.2%	78.8%
Portuguese-GSD	Gold tok+mor	-	-	-	-	-	-	-	90.9%	89.5%	83.7%	84.3%
Romanian-Nonstandard	Raw text	98.2%	96.7%	94.2%	89.4%	88.4%	87.1%	92.4%	82.3%	77.1%	59.0%	65.7%
Romanian-Nonstandard	Gold tok	-	-	95.9%	91.0%	89.9%	88.5%	94.0%	84.9%	79.4%	60.9%	67.3%
Romanian-Nonstandard	Gold tok+mor	-	-	-	-	-	-	-	87.8%	82.8%	75.2%	77.0%
Romanian-RRT	Raw text	99.7%	95.3%	96.7%	95.9%	96.1%	95.7%	96.6%	85.3%	80.0%	71.5%	71.6%
Romanian-RRT	Gold tok	-	-	96.9%	96.2%	96.4%	96.0%	96.8%	86.0%	80.6%	72.0%	72.1%
Romanian-RRT	Gold tok+mor	-	-	-	-	-	-	-	87.9%	83.1%	76.9%	77.9%
Russian-GSD	Raw text	99.5%	96.2%	95.0%	94.7%	85.4%	84.3%	92.3%	82.3%	77.4%	62.1%	67.4%
Russian-GSD	Gold tok	-	-	95.4%	95.1%	85.8%	84.7%	92.7%	83.5%	78.6%	62.9%	68.3%
Russian-GSD	Gold tok+mor	-	-	-	-	-	-	-	87.0%	83.9%	81.0%	81.5%
Russian-SynTagRus	Raw text	99.6%	98.8%	97.8%	-	93.5%	93.2%	96.5%	87.6%	85.0%	77.0%	79.4%
Russian-SynTagRus	Gold tok	-	-	98.2%	-	93.9%	93.5%	96.9%	88.3%	85.7%	77.5%	79.9%
Russian-SynTagRus	Gold tok+mor	-	-	-	-	-	-	-	90.3%	89.0%	86.9%	87.3%
Russian-Taiga	Raw text	97.6%	76.0%	88.3%	91.5%	77.0%	71.0%	84.9%	65.1%	57.7%	38.2%	43.8%
Russian-Taiga	Gold tok	-	-	90.4%	93.8%	79.2%	72.9%	87.0%	69.2%	61.3%	40.7%	46.7%
Russian-Taiga	Gold tok+mor	-	-	-	-	-	-	-	75.4%	70.7%	64.7%	66.1%
Scottish Gaelic-ARCOSG	Raw text	99.6%	54.7%	90.5%	80.1%	84.7%	79.5%	92.1%	73.9%	66.1%	47.7%	52.4%
Scottish Gaelic-ARCOSG	Gold tok	-	-	91.1%	80.7%	85.1%	80.0%	92.5%	78.5%	70.4%	52.2%	58.1%
Scottish Gaelic-ARCOSG	Gold tok+mor	-	-	-	-	-	-	-	82.6%	78.0%	69.4%	71.3%
Serbian-SET	Raw text	100.0%	93.0%	97.1%	90.7%	91.1%	90.5%	95.1%	85.7%	81.8%	69.7%	73.8%
Serbian-SET	Gold tok	-	-	97.2%	90.8%	91.2%	90.7%	95.1%	86.3%	82.4%	70.3%	74.4%
Serbian-SET	Gold tok+mor	-	-	-	-	-	-	-	89.2%	86.4%	82.6%	83.7%
Slovak-SNK	Raw text	100.0%	85.3%	92.9%	77.0%	80.3%	76.7%	86.6%	81.0%	76.3%	56.1%	60.7%
Slovak-SNK	Gold tok	-	-	93.0%	77.2%	80.5%	76.8%	86.6%	82.5%	77.8%	57.2%	61.5%
Slovak-SNK	Gold tok+mor	-	-	-	-	-	-	-	88.9%	86.7%	83.7%	84.5%
Slovenian-SSJ	Raw text	98.0%	68.0%	94.2%	86.2%	86.5%	85.7%	93.4%	79.6%	76.4%	62.8%	68.2%
Slovenian-SSJ	Gold tok	-	-	96.2%	88.3%	88.7%	87.8%	95.3%	85.2%	81.8%	67.2%	72.8%
Slovenian-SSJ	Gold tok+mor	-	-	-	-	-	-	-	92.1%	90.6%	87.5%	87.9%
Slovenian-SST	Raw text	99.8%	23.1%	87.5%	79.7%	79.8%	76.8%	90.8%	54.1%	47.0%	33.9%	38.1%
Slovenian-SST	Gold tok	-	-	88.7%	80.3%	80.5%	77.9%	91.1%	64.5%	56.9%	43.0%	48.7%
Slovenian-SST	Gold tok+mor	-	-	-	-	-	-	-	76.0%	70.7%	64.3%	66.6%
Spanish-AnCora	Raw text	100.0%	98.3%	98.3%	98.1%	98.1%	97.4%	98.5%	88.2%	85.1%	77.0%	77.5%
Spanish-AnCora	Gold tok	-	-	98.4%	98.2%	98.2%	97.4%	98.5%	88.4%	85.3%	77.2%	77.7%
Spanish-AnCora	Gold tok+mor	-	-	-	-	-	-	-	90.2%	87.6%	81.4%	82.3%
Spanish-GSD	Raw text	99.8%	94.5%	95.5%	-	96.2%	93.7%	95.9%	85.4%	82.0%	68.6%	69.3%
Spanish-GSD	Gold tok	-	-	95.7%	-	96.5%	94.0%	96.1%	86.0%	82.5%	69.1%	69.7%
Spanish-GSD	Gold tok+mor	-	-	-	-	-	-	-	88.4%	85.8%	78.7%	79.6%
Swedish-LinES	Raw text	100.0%	87.2%	94.5%	92.1%	88.5%	85.3%	95.1%	80.4%	75.8%	60.7%	68.1%
Swedish-LinES	Gold tok	-	-	94.7%	92.2%	88.6%	85.4%	95.2%	81.2%	76.5%	61.2%	68.7%
Swedish-LinES	Gold tok+mor	-	-	-	-	-	-	-	86.0%	82.4%	78.6%	79.9%
Swedish-Talbanken	Raw text	99.9%	96.1%	95.6%	93.9%	94.5%	92.9%	95.4%	82.5%	78.6%	70.0%	70.4%
Swedish-Talbanken	Gold tok	-	-	95.7%	94.0%	94.5%	93.0%	95.5%	82.9%	78.9%	70.3%	70.7%
Swedish-Talbanken	Gold tok+mor	-	-	-	-	-	-	-	88.4%	85.6%	81.8%	82.8%
Tamil-TTB	Raw text	94.5%	97.5%	81.3%	76.3%	80.5%	75.6%	84.1%	58.9%	52.0%	42.3%	43.4%
Tamil-TTB	Gold tok	-	-	85.7%	80.1%	84.7%	79.3%	88.3%	65.0%	56.9%	46.7%	47.9%
Tamil-TTB	Gold tok+mor	-	-	-	-	-	-	-	79.0%	73.1%	69.0%	70.0%
Telugu-MTG	Raw text	99.6%	96.6%	90.3%	90.3%	98.5%	90.3%	-	87.1%	75.8%	64.8%	69.6%
Telugu-MTG	Gold tok	-	-	90.6%	90.6%	98.9%	90.6%	-	88.2%	76.8%	65.9%	70.7%
Telugu-MTG	Gold tok+mor	-	-	-	-	-	-	-	90.3%	81.5%	75.6%	75.8%
Turkish-IMST	Raw text	98.3%	97.0%	91.6%	90.7%	88.5%	86.1%	90.0%	62.2%	55.1%	45.2%	46.7%
Turkish-IMST	Gold tok	-	-	93.0%	92.1%	89.9%	87.4%	91.4%	64.5%	57.1%	46.3%	47.9%
Turkish-IMST	Gold tok+mor	-	-	-	-	-	-	-	66.9%	61.4%	56.2%	57.8%
Ukrainian-IU	Raw text	99.8%	96.6%	94.9%	84.0%	84.3%	83.3%	93.6%	79.4%	74.8%	57.6%	64.2%
Ukrainian-IU	Gold tok	-	-	95.1%	84.2%	84.4%	83.5%	93.7%	79.8%	75.1%	57.8%	64.5%
Ukrainian-IU	Gold tok+mor	-	-	-	-	-	-	-	85.2%	83.1%	78.9%	79.5%
Urdu-UDTB	Raw text	100.0%	98.3%	92.4%	90.1%	80.8%	76.1%	93.1%	83.6%	76.9%	49.5%	63.5%
Urdu-UDTB	Gold tok	-	-	92.4%	90.1%	80.8%	76.1%	93.1%	83.7%	77.0%	49.6%	63.6%
Urdu-UDTB	Gold tok+mor	-	-	-	-	-	-	-	87.5%	82.6%	74.8%	76.3%
Uyghur-UDT	Raw text	99.5%	81.9%	87.7%	89.8%	84.0%	76.1%	91.7%	70.6%	56.7%	37.4%	44.2%
Uyghur-UDT	Gold tok	-	-	88.2%	90.3%	84.4%	76.6%	92.2%	72.0%	57.9%	38.0%	44.9%
Uyghur-UDT	Gold tok+mor	-	-	-	-	-	-	-	74.4%	61.1%	50.3%	52.6%
Vietnamese-VTB	Raw text	85.4%	93.5%	76.4%	74.3%	85.0%	74.3%	84.5%	45.8%	40.6%	34.6%	36.7%
Vietnamese-VTB	Gold tok	-	-	87.6%	85.0%	99.5%	84.9%	98.9%	62.6%	54.5%	48.2%	50.8%
Vietnamese-VTB	Gold tok+mor	-	-	-	-	-	-	-	69.4%	66.3%	62.9%	65.2%
Wolof-WTB	Raw text	99.2%	92.0%	91.7%	91.4%	91.0%	88.7%	93.2%	77.0%	70.9%	58.8%	60.3%
Wolof-WTB	Gold tok	-	-	92.6%	92.2%	91.7%	89.5%	93.9%	78.7%	72.5%	60.2%	61.3%
Wolof-WTB	Gold tok+mor	-	-	-	-	-	-	-	87.1%	83.7%	76.6%	78.1%

2. Universal Dependencies 2.4 Models

Universal Dependencies 2.4 Models are distributed under the CC BY-NC-SA licence. The models are based solely on Universal Dependencies 2.4 treebanks. The models work in UDPipe version 1.2 and later.

Universal Dependencies 2.4 Models are versioned according to the date released in the format YYMMDD, where YY, MM and DD are two-digit representation of year, month and day, respectively. The latest version is 190531.

2.1. Download

The latest version 190531 of the Universal Dependencies 2.4 models can be downloaded from LINDAT/CLARIN repository.

2.2. Acknowledgements

This work has been partially supported and has been using language resources and tools developed, stored and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).

The models were trained on Universal Dependencies 2.4 treebanks.

For the UD treebanks which do not contain original plain text version, raw text is used to train the tokenizer instead. The plain texts were taken from the W2C – Web to Corpus.

2.2.1. Publications

• (Straka et al. 2017) Milan Straka and Jana Straková. Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe. In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, Vancouver, Canada, August 2017.
• (Straka et al. 2016) Straka Milan, Hajič Jan, Straková Jana. UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), Portorož, Slovenia, May 2016.

2.3. Model Description

The Universal Dependencies 2.4 models contain 90 models of 60 languages, each consisting of a tokenizer, tagger, lemmatizer and dependency parser, all trained using the UD data. We used the original train-dev-test split, but for treebanks with only train and no dev data we used last 10% of the train data as dev data. We produce models only for treebanks with at least 1000 training words.

The tokenizer is trained using the SpaceAfter=No features. If the features are not present in the data, they can be filled in using raw text in the language in question.

The tagger, lemmatizer and parser are trained using gold UD data.

Details about model architecture and training process can be found in the (Straka et al. 2017) paper.

2.3.1. Reproducible Training

In case you want to train the same models, scripts for downloading and resplitting UD 2.4 data, precomputed word embedding, raw texts for tokenizers, all hyperparameter values and training scripts are available in the second archive on the model download page.

2.4. Model Performance

We present the tagger, lemmatizer and parser performance, measured on the testing portion of the data, evaluated in three different settings: using raw text only, using gold tokenization only, and using gold tokenization plus gold morphology (UPOS, XPOS, FEATS and Lemma).

Treebank	Mode	Words	Sents	UPOS	XPOS	UFeats	AllTags	Lemma	UAS	LAS	MLAS	BLEX
Afrikaans-AfriBooms	Raw text	99.6%	98.2%	95.0%	90.6%	94.6%	90.6%	96.5%	81.6%	77.6%	64.4%	66.5%
Afrikaans-AfriBooms	Gold tok	-	-	95.3%	90.8%	94.9%	90.8%	96.7%	82.5%	78.4%	65.1%	67.2%
Afrikaans-AfriBooms	Gold tok+mor	-	-	-	-	-	-	-	87.6%	85.0%	77.0%	79.6%
Ancient Greek-Perseus	Raw text	100.0%	98.8%	82.2%	72.2%	85.7%	72.2%	82.7%	64.0%	57.0%	30.2%	38.2%
Ancient Greek-Perseus	Gold tok	-	-	82.2%	72.2%	85.7%	72.2%	82.7%	64.1%	57.2%	30.3%	38.4%
Ancient Greek-Perseus	Gold tok+mor	-	-	-	-	-	-	-	68.7%	63.9%	53.1%	57.2%
Ancient Greek-PROIEL	Raw text	100.0%	51.6%	96.0%	96.2%	88.5%	87.1%	93.2%	72.2%	67.5%	50.1%	56.0%
Ancient Greek-PROIEL	Gold tok	-	-	96.1%	96.3%	88.7%	87.4%	93.2%	77.0%	72.1%	54.4%	60.3%
Ancient Greek-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	80.2%	76.4%	66.7%	70.3%
Arabic-PADT	Raw text	94.6%	82.1%	90.4%	84.0%	84.2%	83.8%	88.5%	72.7%	68.1%	56.2%	59.2%
Arabic-PADT	Gold tok	-	-	95.6%	89.0%	89.2%	88.8%	92.9%	82.0%	76.8%	63.6%	66.3%
Arabic-PADT	Gold tok+mor	-	-	-	-	-	-	-	83.9%	80.7%	75.7%	76.8%
Armenian-ArmTDP	Raw text	99.5%	96.3%	90.2%	-	81.4%	79.9%	90.3%	72.1%	63.1%	43.6%	50.6%
Armenian-ArmTDP	Gold tok	-	-	90.6%	-	81.7%	80.2%	90.7%	72.5%	63.5%	43.7%	50.7%
Armenian-ArmTDP	Gold tok+mor	-	-	-	-	-	-	-	79.8%	72.9%	65.0%	66.7%
Basque-BDT	Raw text	100.0%	99.8%	92.3%	-	87.3%	84.8%	93.5%	75.0%	69.9%	57.4%	63.2%
Basque-BDT	Gold tok	-	-	92.4%	-	87.4%	84.8%	93.6%	75.1%	70.0%	57.4%	63.2%
Basque-BDT	Gold tok+mor	-	-	-	-	-	-	-	82.1%	78.4%	75.2%	77.2%
Belarusian-HSE	Raw text	99.8%	73.3%	83.9%	31.7%	66.6%	24.0%	75.0%	58.1%	52.3%	28.4%	33.0%
Belarusian-HSE	Gold tok	-	-	84.1%	31.9%	66.8%	24.1%	75.2%	60.1%	54.1%	29.3%	34.1%
Belarusian-HSE	Gold tok+mor	-	-	-	-	-	-	-	72.1%	69.1%	62.2%	63.1%
Bulgarian-BTB	Raw text	99.9%	93.7%	97.6%	94.3%	95.4%	93.8%	94.6%	89.0%	85.0%	75.2%	73.9%
Bulgarian-BTB	Gold tok	-	-	97.8%	94.5%	95.5%	93.9%	94.7%	90.0%	85.9%	76.1%	74.7%
Bulgarian-BTB	Gold tok+mor	-	-	-	-	-	-	-	92.5%	89.1%	84.4%	84.7%
Catalan-AnCora	Raw text	100.0%	99.6%	98.1%	98.0%	97.7%	96.9%	98.2%	89.0%	85.9%	77.4%	77.8%
Catalan-AnCora	Gold tok	-	-	98.1%	98.0%	97.7%	97.0%	98.2%	89.1%	86.0%	77.4%	77.8%
Catalan-AnCora	Gold tok+mor	-	-	-	-	-	-	-	91.0%	88.5%	82.5%	83.0%
Chinese-GSD	Raw text	90.0%	99.1%	84.0%	83.8%	88.7%	82.5%	89.9%	62.8%	58.7%	49.0%	53.7%
Chinese-GSD	Gold tok	-	-	92.1%	91.9%	98.7%	90.7%	100.0%	75.6%	70.1%	59.6%	65.4%
Chinese-GSD	Gold tok+mor	-	-	-	-	-	-	-	84.8%	81.9%	75.9%	78.4%
Classical Chinese-Kyoto	Raw text	99.5%	38.9%	90.8%	87.8%	91.4%	85.2%	99.4%	66.5%	60.0%	56.3%	58.5%
Classical Chinese-Kyoto	Gold tok	-	-	92.5%	89.8%	92.6%	87.4%	100.0%	78.1%	71.3%	67.7%	70.1%
Classical Chinese-Kyoto	Gold tok+mor	-	-	-	-	-	-	-	88.7%	84.2%	82.9%	83.3%
Coptic-Scriptorium	Raw text	64.5%	29.8%	60.9%	60.0%	61.7%	59.6%	62.2%	35.5%	33.4%	21.3%	24.0%
Coptic-Scriptorium	Gold tok	-	-	93.3%	91.8%	95.3%	91.0%	94.8%	81.5%	75.8%	59.5%	63.2%
Coptic-Scriptorium	Gold tok+mor	-	-	-	-	-	-	-	86.5%	82.0%	70.0%	73.1%
Croatian-SET	Raw text	100.0%	94.0%	96.9%	90.1%	90.7%	90.1%	95.3%	83.8%	78.1%	65.1%	69.8%
Croatian-SET	Gold tok	-	-	97.0%	90.2%	90.8%	90.2%	95.3%	84.3%	78.7%	65.5%	70.2%
Croatian-SET	Gold tok+mor	-	-	-	-	-	-	-	87.1%	82.5%	77.2%	79.3%
Czech-CAC	Raw text	100.0%	99.7%	98.2%	90.7%	89.8%	89.4%	97.0%	87.0%	83.7%	70.7%	77.3%
Czech-CAC	Gold tok	-	-	98.2%	90.8%	89.8%	89.5%	97.0%	87.1%	83.7%	70.8%	77.4%
Czech-CAC	Gold tok+mor	-	-	-	-	-	-	-	89.8%	87.5%	84.1%	85.0%
Czech-CLTT	Raw text	99.6%	98.9%	97.2%	87.1%	87.2%	86.9%	96.0%	79.0%	75.5%	60.0%	69.0%
Czech-CLTT	Gold tok	-	-	97.6%	87.5%	87.7%	87.4%	96.4%	79.6%	76.1%	60.4%	69.4%
Czech-CLTT	Gold tok+mor	-	-	-	-	-	-	-	82.7%	79.6%	74.7%	75.3%
Czech-FicTree	Raw text	100.0%	99.1%	97.1%	90.0%	90.8%	89.5%	97.1%	86.3%	82.1%	68.7%	74.3%
Czech-FicTree	Gold tok	-	-	97.1%	90.0%	90.8%	89.5%	97.1%	86.4%	82.1%	68.8%	74.4%
Czech-FicTree	Gold tok+mor	-	-	-	-	-	-	-	90.5%	87.7%	83.3%	84.1%
Czech-PDT	Raw text	99.9%	93.3%	98.2%	92.8%	92.4%	91.9%	97.8%	86.9%	83.8%	74.3%	79.2%
Czech-PDT	Gold tok	-	-	98.3%	92.9%	92.5%	92.0%	97.9%	87.7%	84.6%	75.0%	79.8%
Czech-PDT	Gold tok+mor	-	-	-	-	-	-	-	90.3%	88.2%	85.5%	86.1%
Danish-DDT	Raw text	99.8%	90.8%	95.4%	-	94.8%	93.4%	94.7%	79.2%	75.8%	66.3%	66.6%
Danish-DDT	Gold tok	-	-	95.6%	-	95.0%	93.6%	94.9%	80.2%	76.8%	67.2%	67.5%
Danish-DDT	Gold tok+mor	-	-	-	-	-	-	-	84.8%	82.4%	77.4%	79.1%
Dutch-Alpino	Raw text	99.8%	90.0%	94.2%	91.5%	93.5%	90.8%	95.3%	81.8%	77.6%	62.5%	65.5%
Dutch-Alpino	Gold tok	-	-	94.5%	91.7%	93.7%	91.0%	95.5%	82.8%	78.7%	63.3%	66.4%
Dutch-Alpino	Gold tok+mor	-	-	-	-	-	-	-	86.3%	82.8%	74.1%	75.8%
Dutch-LassySmall	Raw text	99.8%	74.0%	94.2%	91.9%	93.8%	91.2%	95.6%	80.3%	76.2%	63.6%	64.5%
Dutch-LassySmall	Gold tok	-	-	94.3%	92.2%	94.2%	91.5%	95.9%	83.6%	79.1%	67.2%	68.3%
Dutch-LassySmall	Gold tok+mor	-	-	-	-	-	-	-	87.5%	84.1%	78.1%	78.8%
English-EWT	Raw text	99.0%	76.3%	93.5%	92.9%	94.4%	91.5%	95.5%	80.0%	77.0%	67.6%	69.6%
English-EWT	Gold tok	-	-	94.5%	93.9%	95.4%	92.5%	96.3%	83.9%	80.7%	71.2%	73.2%
English-EWT	Gold tok+mor	-	-	-	-	-	-	-	87.4%	85.4%	81.3%	82.1%
English-GUM	Raw text	99.8%	84.4%	93.8%	93.5%	94.5%	92.3%	94.9%	80.2%	76.1%	64.9%	64.8%
English-GUM	Gold tok	-	-	94.0%	93.8%	94.8%	92.6%	95.1%	81.9%	77.8%	66.5%	66.4%
English-GUM	Gold tok+mor	-	-	-	-	-	-	-	86.5%	84.3%	77.9%	78.7%
English-LinES	Raw text	99.9%	87.0%	94.9%	92.4%	94.8%	89.9%	95.8%	79.5%	74.9%	65.8%	66.6%
English-LinES	Gold tok	-	-	94.9%	92.5%	94.8%	90.0%	95.8%	80.1%	75.5%	66.4%	67.1%
English-LinES	Gold tok+mor	-	-	-	-	-	-	-	84.3%	80.9%	76.4%	78.2%
English-ParTUT	Raw text	99.7%	100.0%	93.9%	93.7%	93.8%	92.1%	96.5%	84.7%	81.3%	69.1%	71.1%
English-ParTUT	Gold tok	-	-	94.2%	93.9%	94.0%	92.3%	96.8%	85.1%	81.7%	69.4%	71.5%
English-ParTUT	Gold tok+mor	-	-	-	-	-	-	-	87.9%	86.3%	79.6%	81.2%
Estonian-EDT	Raw text	100.0%	91.4%	95.4%	96.7%	93.5%	91.7%	90.5%	79.2%	75.3%	67.7%	64.7%
Estonian-EDT	Gold tok	-	-	95.5%	96.8%	93.6%	91.8%	90.6%	80.0%	76.2%	68.4%	65.4%
Estonian-EDT	Gold tok+mor	-	-	-	-	-	-	-	85.0%	82.7%	79.4%	80.5%
Estonian-EWT	Raw text	99.1%	67.0%	83.2%	85.6%	79.5%	76.2%	79.8%	60.1%	51.2%	38.8%	36.7%
Estonian-EWT	Gold tok	-	-	84.0%	86.3%	80.2%	77.0%	80.4%	62.6%	53.2%	39.8%	37.6%
Estonian-EWT	Gold tok+mor	-	-	-	-	-	-	-	74.1%	69.9%	64.6%	65.7%
Finnish-FTB	Raw text	100.0%	87.4%	91.5%	90.8%	92.6%	88.9%	88.5%	79.5%	75.0%	64.2%	61.0%
Finnish-FTB	Gold tok	-	-	91.8%	91.0%	92.7%	89.2%	88.6%	81.1%	76.6%	65.9%	62.6%
Finnish-FTB	Gold tok+mor	-	-	-	-	-	-	-	89.9%	87.6%	82.9%	84.2%
Finnish-TDT	Raw text	99.7%	88.6%	94.3%	95.4%	92.0%	90.8%	86.9%	80.5%	76.8%	68.6%	62.8%
Finnish-TDT	Gold tok	-	-	94.7%	95.8%	92.4%	91.2%	87.2%	81.8%	78.1%	69.5%	63.6%
Finnish-TDT	Gold tok+mor	-	-	-	-	-	-	-	86.8%	84.7%	81.6%	82.5%
French-GSD	Raw text	98.9%	94.6%	95.9%	-	95.6%	94.5%	96.7%	87.5%	84.5%	74.0%	76.1%
French-GSD	Gold tok	-	-	97.0%	-	96.6%	95.6%	97.8%	89.3%	86.4%	75.6%	77.3%
French-GSD	Gold tok+mor	-	-	-	-	-	-	-	91.2%	89.2%	83.3%	83.7%
French-ParTUT	Raw text	99.4%	100.0%	94.6%	93.8%	91.9%	90.5%	95.2%	86.0%	82.2%	65.2%	70.0%
French-ParTUT	Gold tok	-	-	95.3%	94.4%	92.5%	91.1%	95.8%	86.6%	82.9%	66.1%	70.5%
French-ParTUT	Gold tok+mor	-	-	-	-	-	-	-	89.5%	87.6%	79.8%	80.9%
French-Sequoia	Raw text	99.1%	87.5%	96.1%	-	95.0%	94.1%	96.9%	85.5%	82.8%	73.1%	75.8%
French-Sequoia	Gold tok	-	-	97.1%	-	95.9%	95.0%	97.8%	87.5%	84.8%	75.0%	77.3%
French-Sequoia	Gold tok+mor	-	-	-	-	-	-	-	90.2%	88.8%	84.3%	84.7%
French-Spoken	Raw text	99.9%	22.4%	93.0%	97.1%	-	90.6%	95.6%	72.6%	66.8%	55.1%	55.9%
French-Spoken	Gold tok	-	-	93.1%	97.2%	-	90.8%	95.7%	78.3%	71.7%	61.8%	62.1%
French-Spoken	Gold tok+mor	-	-	-	-	-	-	-	82.5%	78.0%	69.8%	71.0%
Galician-CTG	Raw text	99.2%	97.5%	96.3%	95.8%	99.0%	95.4%	96.2%	79.2%	76.2%	62.5%	65.4%
Galician-CTG	Gold tok	-	-	97.0%	96.5%	99.8%	96.2%	96.9%	80.8%	77.7%	64.3%	67.2%
Galician-CTG	Gold tok+mor	-	-	-	-	-	-	-	83.0%	80.7%	69.4%	74.1%
Galician-TreeGal	Raw text	98.8%	85.4%	91.1%	87.3%	89.5%	86.6%	92.5%	72.1%	66.6%	49.8%	52.3%
Galician-TreeGal	Gold tok	-	-	92.2%	88.1%	90.4%	87.4%	93.6%	75.1%	69.1%	52.4%	55.2%
Galician-TreeGal	Gold tok+mor	-	-	-	-	-	-	-	81.7%	77.5%	69.4%	70.7%
German-GSD	Raw text	99.6%	80.9%	91.7%	79.5%	69.8%	62.9%	95.4%	78.2%	72.7%	34.0%	61.5%
German-GSD	Gold tok	-	-	92.1%	79.8%	70.2%	63.4%	95.8%	80.7%	75.0%	35.4%	63.6%
German-GSD	Gold tok+mor	-	-	-	-	-	-	-	85.5%	81.2%	72.3%	75.4%
Gothic-PROIEL	Raw text	100.0%	31.1%	94.3%	94.8%	87.4%	85.5%	92.6%	68.6%	62.0%	48.8%	54.6%
Gothic-PROIEL	Gold tok	-	-	94.8%	95.2%	87.6%	85.9%	92.7%	76.8%	70.0%	56.2%	61.7%
Gothic-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	80.0%	76.0%	69.1%	72.5%
Greek-GDT	Raw text	99.8%	88.5%	95.6%	95.6%	90.2%	88.9%	94.5%	86.4%	83.1%	66.3%	69.7%
Greek-GDT	Gold tok	-	-	95.9%	95.9%	90.5%	89.2%	94.7%	87.0%	83.7%	67.1%	70.5%
Greek-GDT	Gold tok+mor	-	-	-	-	-	-	-	89.5%	87.6%	81.6%	82.5%
Hebrew-HTB	Raw text	85.0%	99.4%	80.5%	80.5%	78.7%	77.7%	81.6%	61.7%	58.3%	44.6%	47.5%
Hebrew-HTB	Gold tok	-	-	94.9%	94.9%	92.7%	91.5%	95.4%	83.6%	79.6%	64.3%	67.1%
Hebrew-HTB	Gold tok+mor	-	-	-	-	-	-	-	87.0%	84.9%	78.4%	78.8%
Hindi-HDTB	Raw text	100.0%	98.9%	95.9%	94.9%	90.4%	87.8%	98.1%	91.3%	87.2%	69.2%	80.1%
Hindi-HDTB	Gold tok	-	-	95.9%	95.0%	90.4%	87.8%	98.1%	91.3%	87.2%	69.3%	80.2%
Hindi-HDTB	Gold tok+mor	-	-	-	-	-	-	-	93.8%	90.8%	85.4%	86.6%
Hungarian-Szeged	Raw text	99.8%	95.2%	90.5%	-	88.0%	86.4%	88.5%	72.7%	67.1%	53.6%	57.8%
Hungarian-Szeged	Gold tok	-	-	90.7%	-	88.2%	86.5%	88.7%	73.3%	67.6%	53.9%	58.1%
Hungarian-Szeged	Gold tok+mor	-	-	-	-	-	-	-	80.5%	77.6%	72.7%	76.6%
Indonesian-GSD	Raw text	100.0%	93.9%	93.0%	92.2%	93.9%	87.1%	92.2%	81.0%	74.5%	63.6%	62.9%
Indonesian-GSD	Gold tok	-	-	93.0%	92.2%	93.9%	87.1%	92.2%	81.2%	74.8%	63.9%	63.2%
Indonesian-GSD	Gold tok+mor	-	-	-	-	-	-	-	84.0%	79.8%	76.4%	78.3%
Irish-IDT	Raw text	99.6%	95.9%	89.6%	88.5%	79.5%	75.8%	85.6%	75.2%	65.3%	40.2%	44.3%
Irish-IDT	Gold tok	-	-	90.0%	88.9%	79.8%	76.2%	86.0%	75.7%	65.6%	40.4%	44.4%
Irish-IDT	Gold tok+mor	-	-	-	-	-	-	-	79.6%	72.9%	61.4%	63.5%
Italian-ISDT	Raw text	99.8%	99.4%	97.1%	97.0%	97.0%	96.1%	97.3%	89.2%	86.7%	77.3%	77.5%
Italian-ISDT	Gold tok	-	-	97.4%	97.2%	97.2%	96.4%	97.5%	89.5%	87.0%	77.7%	77.8%
Italian-ISDT	Gold tok+mor	-	-	-	-	-	-	-	91.8%	90.2%	85.0%	85.5%
Italian-ParTUT	Raw text	99.8%	99.0%	97.0%	96.5%	96.4%	95.2%	96.5%	87.5%	84.4%	73.2%	72.4%
Italian-ParTUT	Gold tok	-	-	97.1%	96.6%	96.5%	95.3%	96.7%	87.4%	84.3%	73.1%	72.3%
Italian-ParTUT	Gold tok+mor	-	-	-	-	-	-	-	89.7%	87.6%	79.8%	80.7%
Italian-PoSTWITA	Raw text	99.5%	30.2%	94.0%	93.7%	94.3%	92.3%	95.1%	74.1%	69.1%	56.5%	57.2%
Italian-PoSTWITA	Gold tok	-	-	94.6%	94.2%	94.9%	92.9%	95.6%	80.6%	75.1%	64.4%	65.3%
Italian-PoSTWITA	Gold tok+mor	-	-	-	-	-	-	-	84.7%	80.5%	74.5%	75.0%
Italian-VIT	Raw text	99.7%	94.0%	96.0%	94.9%	95.9%	93.5%	96.9%	84.1%	80.1%	68.3%	69.8%
Italian-VIT	Gold tok	-	-	96.3%	95.2%	96.1%	93.8%	97.1%	84.9%	80.8%	69.0%	70.5%
Italian-VIT	Gold tok+mor	-	-	-	-	-	-	-	88.1%	85.3%	78.4%	79.4%
Japanese-GSD	Raw text	91.4%	94.7%	88.8%	88.5%	91.4%	88.5%	90.7%	76.3%	74.8%	62.2%	64.0%
Japanese-GSD	Gold tok	-	-	96.9%	96.3%	100.0%	96.3%	99.1%	92.7%	90.7%	81.2%	83.3%
Japanese-GSD	Gold tok+mor	-	-	-	-	-	-	-	95.3%	94.3%	88.0%	88.1%
Korean-GSD	Raw text	99.8%	94.0%	93.5%	81.7%	99.5%	79.5%	87.0%	69.5%	61.4%	54.1%	50.8%
Korean-GSD	Gold tok	-	-	93.7%	81.9%	99.7%	79.7%	87.2%	70.3%	62.1%	54.8%	51.4%
Korean-GSD	Gold tok+mor	-	-	-	-	-	-	-	72.5%	65.5%	60.4%	61.6%
Korean-Kaist	Raw text	100.0%	100.0%	93.3%	80.1%	-	80.1%	88.5%	77.9%	70.6%	61.9%	58.1%
Korean-Kaist	Gold tok	-	-	93.4%	80.1%	-	80.1%	88.5%	78.0%	70.7%	62.0%	58.1%
Korean-Kaist	Gold tok+mor	-	-	-	-	-	-	-	80.3%	73.7%	67.8%	68.4%
Latin-ITTB	Raw text	100.0%	90.7%	97.1%	93.0%	93.3%	91.4%	98.0%	83.2%	79.9%	70.5%	75.3%
Latin-ITTB	Gold tok	-	-	97.1%	93.0%	93.3%	91.4%	98.0%	83.9%	80.5%	70.7%	75.5%
Latin-ITTB	Gold tok+mor	-	-	-	-	-	-	-	87.8%	85.8%	81.9%	83.0%
Latin-PROIEL	Raw text	99.9%	36.8%	94.5%	94.7%	86.7%	85.6%	94.5%	65.9%	60.1%	47.7%	54.4%
Latin-PROIEL	Gold tok	-	-	94.7%	94.8%	87.2%	86.2%	94.7%	73.4%	67.3%	54.9%	61.3%
Latin-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	77.2%	73.4%	67.1%	70.3%
Latin-Perseus	Raw text	100.0%	98.5%	83.3%	67.2%	72.1%	67.2%	78.0%	57.7%	47.1%	29.4%	31.9%
Latin-Perseus	Gold tok	-	-	83.3%	67.2%	72.1%	67.2%	77.9%	57.9%	47.2%	29.4%	31.9%
Latin-Perseus	Gold tok+mor	-	-	-	-	-	-	-	67.6%	61.8%	55.9%	59.1%
Latvian-LVTB	Raw text	99.4%	99.0%	93.5%	84.0%	89.2%	83.6%	92.7%	79.3%	74.3%	61.4%	65.5%
Latvian-LVTB	Gold tok	-	-	94.0%	84.4%	89.7%	84.1%	93.2%	80.0%	74.9%	62.1%	66.1%
Latvian-LVTB	Gold tok+mor	-	-	-	-	-	-	-	86.3%	83.0%	79.1%	80.3%
Lithuanian-ALKSNIS	Raw text	99.3%	87.0%	87.4%	76.2%	77.9%	75.7%	85.3%	63.6%	56.2%	40.8%	44.7%
Lithuanian-ALKSNIS	Gold tok	-	-	87.9%	76.7%	78.3%	76.1%	85.8%	64.9%	57.5%	41.5%	45.5%
Lithuanian-ALKSNIS	Gold tok+mor	-	-	-	-	-	-	-	72.7%	69.2%	65.1%	66.5%
Lithuanian-HSE	Raw text	98.1%	92.0%	73.6%	72.0%	68.4%	61.5%	72.3%	46.0%	34.0%	20.8%	23.1%
Lithuanian-HSE	Gold tok	-	-	74.2%	72.5%	69.2%	62.0%	73.1%	47.1%	34.6%	20.9%	23.2%
Lithuanian-HSE	Gold tok+mor	-	-	-	-	-	-	-	54.9%	47.7%	41.9%	44.2%
Maltese-MUDT	Raw text	99.8%	85.2%	93.8%	93.5%	-	93.2%	-	77.3%	71.5%	58.2%	61.8%
Maltese-MUDT	Gold tok	-	-	93.9%	93.7%	-	93.4%	-	77.9%	72.0%	58.6%	62.2%
Maltese-MUDT	Gold tok+mor	-	-	-	-	-	-	-	82.1%	77.7%	68.0%	69.5%
Marathi-UFAL	Raw text	91.0%	84.0%	72.3%	-	61.6%	59.1%	76.8%	59.4%	48.9%	23.0%	30.1%
Marathi-UFAL	Gold tok	-	-	77.7%	-	63.4%	60.4%	76.5%	68.5%	54.9%	26.0%	31.0%
Marathi-UFAL	Gold tok+mor	-	-	-	-	-	-	-	77.9%	67.7%	60.7%	63.1%
North Sami-Giella	Raw text	99.9%	98.8%	87.8%	89.4%	82.5%	78.4%	82.0%	64.7%	57.9%	46.7%	43.2%
North Sami-Giella	Gold tok	-	-	87.9%	89.6%	82.6%	78.5%	82.1%	64.9%	58.2%	46.9%	43.5%
North Sami-Giella	Gold tok+mor	-	-	-	-	-	-	-	81.4%	78.7%	74.2%	77.2%
Norwegian-Bokmaal	Raw text	99.8%	96.9%	96.5%	-	95.2%	94.0%	96.7%	87.2%	84.3%	75.2%	77.2%
Norwegian-Bokmaal	Gold tok	-	-	96.7%	-	95.4%	94.2%	97.0%	87.8%	84.9%	75.7%	77.7%
Norwegian-Bokmaal	Gold tok+mor	-	-	-	-	-	-	-	91.7%	89.9%	85.8%	86.6%
Norwegian-Nynorsk	Raw text	99.9%	93.4%	96.1%	-	94.9%	93.6%	96.3%	85.8%	82.8%	72.9%	74.5%
Norwegian-Nynorsk	Gold tok	-	-	96.2%	-	95.0%	93.7%	96.4%	86.4%	83.5%	73.6%	75.2%
Norwegian-Nynorsk	Gold tok+mor	-	-	-	-	-	-	-	91.1%	89.2%	84.7%	85.8%
Norwegian-NynorskLIA	Raw text	99.8%	99.5%	93.7%	-	93.2%	90.4%	96.2%	73.4%	68.3%	55.8%	59.9%
Norwegian-NynorskLIA	Gold tok	-	-	93.8%	-	93.3%	90.5%	96.4%	73.7%	68.6%	56.0%	60.0%
Norwegian-NynorskLIA	Gold tok+mor	-	-	-	-	-	-	-	80.7%	76.3%	68.7%	70.9%
Old Church Slavonic-PROIEL	Raw text	100.0%	41.0%	93.6%	93.7%	86.8%	85.6%	90.9%	71.9%	65.9%	55.3%	60.0%
Old Church Slavonic-PROIEL	Gold tok	-	-	93.8%	94.0%	87.4%	86.2%	91.0%	79.5%	73.2%	62.4%	66.0%
Old Church Slavonic-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	85.1%	81.3%	76.8%	79.6%
Old French-SRCMF	Raw text	99.9%	100.0%	94.2%	93.8%	96.0%	93.3%	-	85.5%	79.3%	70.9%	74.6%
Old French-SRCMF	Gold tok	-	-	94.3%	93.9%	96.1%	93.4%	-	85.6%	79.4%	71.0%	74.7%
Old French-SRCMF	Gold tok+mor	-	-	-	-	-	-	-	88.8%	84.4%	78.4%	79.7%
Old Russian-TOROT	Raw text	100.0%	29.6%	89.8%	89.8%	82.1%	79.9%	81.1%	63.4%	56.7%	43.3%	44.0%
Old Russian-TOROT	Gold tok	-	-	90.4%	90.5%	82.8%	80.8%	81.1%	73.3%	66.1%	51.9%	50.8%
Old Russian-TOROT	Gold tok+mor	-	-	-	-	-	-	-	80.5%	76.4%	70.4%	73.1%
Persian-Seraji	Raw text	99.7%	98.8%	96.0%	95.9%	96.1%	95.4%	93.6%	83.6%	79.6%	72.8%	70.1%
Persian-Seraji	Gold tok	-	-	96.3%	96.3%	96.4%	95.7%	93.9%	84.3%	80.2%	73.3%	70.5%
Persian-Seraji	Gold tok+mor	-	-	-	-	-	-	-	87.2%	84.3%	80.0%	80.8%
Polish-LFG	Raw text	99.8%	99.7%	96.7%	87.2%	89.1%	86.5%	94.5%	90.9%	87.4%	74.4%	78.5%
Polish-LFG	Gold tok	-	-	96.9%	87.3%	89.2%	86.7%	94.6%	91.3%	87.8%	74.7%	78.8%
Polish-LFG	Gold tok+mor	-	-	-	-	-	-	-	96.2%	94.8%	92.9%	93.1%
Polish-PDB	Raw text	99.9%	97.0%	97.2%	88.3%	88.8%	87.8%	95.8%	87.6%	83.5%	69.2%	76.0%
Polish-PDB	Gold tok	-	-	97.3%	88.4%	88.9%	87.9%	96.0%	88.1%	84.0%	69.6%	76.4%
Polish-PDB	Gold tok+mor	-	-	-	-	-	-	-	90.9%	88.8%	85.5%	86.0%
Portuguese-Bosque	Raw text	99.5%	90.2%	95.7%	-	94.4%	92.3%	96.6%	86.5%	82.6%	67.4%	72.4%
Portuguese-Bosque	Gold tok	-	-	96.2%	-	94.8%	92.8%	97.1%	87.7%	83.8%	68.3%	73.6%
Portuguese-Bosque	Gold tok+mor	-	-	-	-	-	-	-	89.3%	86.2%	79.3%	80.2%
Portuguese-GSD	Raw text	99.9%	96.5%	97.0%	97.0%	99.8%	97.0%	98.6%	88.0%	85.9%	77.9%	78.5%
Portuguese-GSD	Gold tok	-	-	97.2%	97.2%	99.9%	97.2%	98.7%	88.4%	86.3%	78.2%	78.8%
Portuguese-GSD	Gold tok+mor	-	-	-	-	-	-	-	90.9%	89.5%	83.7%	84.3%
Romanian-Nonstandard	Raw text	98.3%	96.7%	93.8%	88.9%	87.8%	86.5%	91.8%	81.7%	76.0%	57.5%	64.0%
Romanian-Nonstandard	Gold tok	-	-	95.5%	90.5%	89.3%	88.0%	93.3%	84.0%	78.2%	59.2%	65.6%
Romanian-Nonstandard	Gold tok+mor	-	-	-	-	-	-	-	87.1%	81.7%	73.5%	75.5%
Romanian-RRT	Raw text	99.7%	95.3%	96.7%	95.9%	96.1%	95.7%	96.6%	85.3%	80.0%	71.5%	71.6%
Romanian-RRT	Gold tok	-	-	96.9%	96.2%	96.4%	96.0%	96.8%	86.0%	80.6%	72.0%	72.1%
Romanian-RRT	Gold tok+mor	-	-	-	-	-	-	-	87.9%	83.1%	76.9%	77.9%
Russian-GSD	Raw text	99.5%	96.2%	95.0%	94.7%	85.4%	84.3%	92.3%	82.4%	77.2%	61.8%	66.8%
Russian-GSD	Gold tok	-	-	95.4%	95.1%	85.8%	84.7%	92.7%	83.3%	78.1%	62.4%	67.6%
Russian-GSD	Gold tok+mor	-	-	-	-	-	-	-	86.7%	83.5%	80.5%	81.1%
Russian-SynTagRus	Raw text	99.6%	98.8%	97.8%	-	93.5%	93.2%	96.5%	87.6%	85.0%	77.0%	79.4%
Russian-SynTagRus	Gold tok	-	-	98.2%	-	93.9%	93.5%	96.9%	88.3%	85.7%	77.5%	79.9%
Russian-SynTagRus	Gold tok+mor	-	-	-	-	-	-	-	90.3%	89.0%	86.9%	87.3%
Russian-Taiga	Raw text	97.6%	76.0%	88.3%	91.5%	77.0%	71.0%	84.9%	65.5%	58.2%	38.5%	44.0%
Russian-Taiga	Gold tok	-	-	90.4%	93.8%	79.2%	72.9%	87.0%	69.9%	62.1%	41.4%	47.5%
Russian-Taiga	Gold tok+mor	-	-	-	-	-	-	-	76.0%	71.7%	66.2%	67.7%
Serbian-SET	Raw text	100.0%	93.0%	97.4%	91.1%	91.5%	91.1%	95.1%	86.5%	82.4%	70.0%	74.0%
Serbian-SET	Gold tok	-	-	97.4%	91.2%	91.6%	91.2%	95.1%	87.1%	83.1%	70.7%	74.7%
Serbian-SET	Gold tok+mor	-	-	-	-	-	-	-	89.7%	86.5%	82.3%	83.7%
Slovak-SNK	Raw text	100.0%	85.3%	92.9%	77.0%	80.3%	76.7%	86.6%	81.0%	76.3%	56.1%	60.7%
Slovak-SNK	Gold tok	-	-	93.0%	77.2%	80.5%	76.8%	86.6%	82.5%	77.8%	57.2%	61.5%
Slovak-SNK	Gold tok+mor	-	-	-	-	-	-	-	88.9%	86.7%	83.7%	84.5%
Slovenian-SSJ	Raw text	100.0%	98.1%	96.1%	88.3%	88.7%	87.7%	95.3%	84.9%	81.5%	66.9%	72.5%
Slovenian-SSJ	Gold tok	-	-	96.2%	88.3%	88.7%	87.8%	95.3%	85.0%	81.6%	67.0%	72.6%
Slovenian-SSJ	Gold tok+mor	-	-	-	-	-	-	-	92.0%	90.4%	87.2%	87.6%
Slovenian-SST	Raw text	99.8%	23.1%	88.4%	80.2%	80.3%	77.7%	91.0%	53.9%	47.0%	34.4%	38.5%
Slovenian-SST	Gold tok	-	-	88.8%	80.7%	80.9%	78.3%	91.2%	64.7%	56.9%	43.1%	48.6%
Slovenian-SST	Gold tok+mor	-	-	-	-	-	-	-	74.8%	69.4%	63.7%	65.6%
Spanish-AnCora	Raw text	100.0%	98.3%	98.3%	98.1%	98.1%	97.4%	98.5%	88.2%	85.1%	77.0%	77.5%
Spanish-AnCora	Gold tok	-	-	98.4%	98.2%	98.2%	97.4%	98.5%	88.4%	85.3%	77.2%	77.7%
Spanish-AnCora	Gold tok+mor	-	-	-	-	-	-	-	90.2%	87.6%	81.4%	82.3%
Spanish-GSD	Raw text	99.8%	94.9%	95.4%	-	96.2%	93.7%	95.9%	85.3%	81.9%	68.7%	69.3%
Spanish-GSD	Gold tok	-	-	95.7%	-	96.5%	93.9%	96.1%	85.9%	82.5%	69.2%	69.8%
Spanish-GSD	Gold tok+mor	-	-	-	-	-	-	-	88.3%	85.6%	78.6%	79.5%
Swedish-LinES	Raw text	100.0%	86.8%	94.4%	91.6%	87.6%	84.4%	94.5%	80.1%	75.2%	59.6%	67.2%
Swedish-LinES	Gold tok	-	-	94.5%	91.7%	87.7%	84.5%	94.5%	80.8%	75.8%	60.0%	67.6%
Swedish-LinES	Gold tok+mor	-	-	-	-	-	-	-	85.7%	81.8%	78.1%	79.6%
Swedish-Talbanken	Raw text	99.9%	96.1%	95.6%	93.9%	94.5%	92.9%	95.4%	82.5%	78.6%	70.0%	70.4%
Swedish-Talbanken	Gold tok	-	-	95.7%	94.0%	94.5%	93.0%	95.5%	82.9%	78.9%	70.3%	70.7%
Swedish-Talbanken	Gold tok+mor	-	-	-	-	-	-	-	88.4%	85.6%	81.8%	82.8%
Tamil-TTB	Raw text	94.5%	97.5%	81.3%	76.3%	80.5%	75.6%	84.1%	58.9%	52.0%	42.3%	43.4%
Tamil-TTB	Gold tok	-	-	85.7%	80.1%	84.7%	79.3%	88.3%	65.0%	56.9%	46.7%	47.9%
Tamil-TTB	Gold tok+mor	-	-	-	-	-	-	-	79.0%	73.1%	69.0%	70.0%
Telugu-MTG	Raw text	99.8%	96.6%	90.5%	90.5%	98.7%	90.5%	-	87.3%	75.7%	64.8%	69.4%
Telugu-MTG	Gold tok	-	-	90.6%	90.6%	98.9%	90.6%	-	88.2%	76.8%	65.9%	70.7%
Telugu-MTG	Gold tok+mor	-	-	-	-	-	-	-	90.3%	81.5%	75.6%	75.8%
Turkish-IMST	Raw text	98.3%	97.0%	91.6%	90.7%	88.5%	86.1%	90.0%	62.2%	55.1%	45.2%	46.7%
Turkish-IMST	Gold tok	-	-	93.0%	92.1%	89.9%	87.4%	91.4%	64.5%	57.1%	46.3%	47.9%
Turkish-IMST	Gold tok+mor	-	-	-	-	-	-	-	66.9%	61.4%	56.2%	57.8%
Ukrainian-IU	Raw text	99.8%	96.6%	94.9%	84.0%	84.3%	83.3%	93.6%	79.4%	74.8%	57.6%	64.2%
Ukrainian-IU	Gold tok	-	-	95.1%	84.2%	84.4%	83.5%	93.7%	79.8%	75.1%	57.8%	64.5%
Ukrainian-IU	Gold tok+mor	-	-	-	-	-	-	-	85.2%	83.1%	78.9%	79.5%
Urdu-UDTB	Raw text	100.0%	98.6%	92.4%	90.1%	80.8%	76.1%	93.1%	83.6%	76.9%	49.5%	63.5%
Urdu-UDTB	Gold tok	-	-	92.4%	90.1%	80.8%	76.1%	93.1%	83.7%	77.0%	49.6%	63.6%
Urdu-UDTB	Gold tok+mor	-	-	-	-	-	-	-	87.5%	82.6%	74.8%	76.3%
Uyghur-UDT	Raw text	99.7%	82.9%	87.9%	90.0%	84.1%	76.3%	91.9%	70.8%	56.7%	37.4%	44.1%
Uyghur-UDT	Gold tok	-	-	88.2%	90.3%	84.4%	76.6%	92.2%	72.0%	57.9%	38.0%	44.9%
Uyghur-UDT	Gold tok+mor	-	-	-	-	-	-	-	74.4%	61.1%	50.3%	52.6%
Vietnamese-VTB	Raw text	85.4%	93.0%	76.4%	74.4%	85.1%	74.3%	84.6%	46.4%	41.2%	35.1%	37.1%
Vietnamese-VTB	Gold tok	-	-	87.6%	85.0%	99.5%	84.9%	98.9%	62.6%	54.5%	48.2%	50.8%
Vietnamese-VTB	Gold tok+mor	-	-	-	-	-	-	-	69.4%	66.3%	62.9%	65.2%
Wolof-WTB	Raw text	99.2%	92.0%	91.7%	91.4%	91.0%	88.7%	93.2%	77.0%	70.9%	58.8%	60.3%
Wolof-WTB	Gold tok	-	-	92.6%	92.2%	91.7%	89.5%	93.9%	78.7%	72.5%	60.2%	61.3%
Wolof-WTB	Gold tok+mor	-	-	-	-	-	-	-	87.1%	83.7%	76.6%	78.1%

3. Universal Dependencies 2.3 Models

Universal Dependencies 2.3 Models are distributed under the CC BY-NC-SA licence. The models are based solely on Universal Dependencies 2.3 treebanks. The models work in UDPipe version 1.2 and later.

Universal Dependencies 2.3 Models are versioned according to the date released in the format YYMMDD, where YY, MM and DD are two-digit representation of year, month and day, respectively. The latest version is 181115.

3.1. Download

The latest version 181115 of the Universal Dependencies 2.3 models can be downloaded from LINDAT/CLARIN repository.

3.2. Acknowledgements

This work has been partially supported and has been using language resources and tools developed, stored and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).

The models were trained on Universal Dependencies 2.3 treebanks.

For the UD treebanks which do not contain original plain text version, raw text is used to train the tokenizer instead. The plain texts were taken from the W2C – Web to Corpus.

3.2.1. Publications

• (Straka et al. 2017) Milan Straka and Jana Straková. Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe. In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, Vancouver, Canada, August 2017.
• (Straka et al. 2016) Straka Milan, Hajič Jan, Straková Jana. UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), Portorož, Slovenia, May 2016.

3.3. Model Description

The Universal Dependencies 2.3 models contain 84 models of 56 languages, each consisting of a tokenizer, tagger, lemmatizer and dependency parser, all trained using the UD data. We used the original train-dev-test split, but for treebanks with only train and no dev data we used last 10% of the train data as dev data. We produce models only for treebanks with at least 1000 training words.

The tokenizer is trained using the SpaceAfter=No features. If the features are not present in the data, they can be filled in using raw text in the language in question.

The tagger, lemmatizer and parser are trained using gold UD data.

Details about model architecture and training process can be found in the (Straka et al. 2017) paper.

3.3.1. Reproducible Training

In case you want to train the same models, scripts for downloading and resplitting UD 2.3 data, precomputed word embedding, raw texts for tokenizers, all hyperparameter values and training scripts are available in the second archive on the model download page.

3.4. Model Performance

We present the tagger, lemmatizer and parser performance, measured on the testing portion of the data, evaluated in three different settings: using raw text only, using gold tokenization only, and using gold tokenization plus gold morphology (UPOS, XPOS, FEATS and Lemma).

Treebank	Mode	Words	Sents	UPOS	XPOS	UFeats	AllTags	Lemma	UAS	LAS	MLAS	BLEX
Afrikaans-AfriBooms	Raw text	99.8%	98.2%	95.2%	90.7%	94.8%	90.7%	96.5%	82.1%	78.0%	64.8%	66.8%
Afrikaans-AfriBooms	Gold tok	-	-	95.3%	90.8%	94.9%	90.8%	96.7%	82.5%	78.4%	65.1%	67.2%
Afrikaans-AfriBooms	Gold tok+mor	-	-	-	-	-	-	-	87.6%	85.0%	77.0%	79.6%
Ancient Greek-Perseus	Raw text	100.0%	98.6%	82.4%	72.3%	85.8%	72.3%	82.6%	63.7%	57.2%	30.6%	38.1%
Ancient Greek-Perseus	Gold tok	-	-	82.4%	72.4%	85.8%	72.3%	82.7%	63.8%	57.3%	30.7%	38.2%
Ancient Greek-Perseus	Gold tok+mor	-	-	-	-	-	-	-	68.9%	64.1%	53.7%	57.4%
Ancient Greek-PROIEL	Raw text	100.0%	49.7%	95.8%	96.0%	88.5%	87.0%	92.7%	72.9%	68.1%	50.2%	56.7%
Ancient Greek-PROIEL	Gold tok	-	-	95.9%	96.2%	88.7%	87.2%	92.8%	77.4%	72.6%	55.1%	60.8%
Ancient Greek-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	79.4%	75.8%	66.1%	69.5%
Arabic-PADT	Raw text	94.6%	82.1%	90.2%	83.8%	83.9%	83.6%	88.4%	72.7%	67.6%	55.6%	58.8%
Arabic-PADT	Gold tok	-	-	95.4%	88.7%	88.9%	88.5%	92.8%	82.2%	76.2%	63.0%	66.1%
Arabic-PADT	Gold tok+mor	-	-	-	-	-	-	-	84.3%	80.4%	75.5%	76.6%
Armenian-ArmTDP	Raw text	99.4%	94.5%	89.0%	-	81.0%	79.3%	90.0%	68.5%	59.4%	39.5%	45.7%
Armenian-ArmTDP	Gold tok	-	-	89.5%	-	81.3%	79.7%	90.3%	69.5%	60.1%	39.7%	46.0%
Armenian-ArmTDP	Gold tok+mor	-	-	-	-	-	-	-	77.2%	70.3%	61.6%	63.5%
Basque-BDT	Raw text	100.0%	99.8%	92.3%	-	87.3%	84.8%	93.5%	75.0%	69.9%	57.4%	63.2%
Basque-BDT	Gold tok	-	-	92.4%	-	87.4%	84.8%	93.6%	75.1%	70.0%	57.4%	63.2%
Basque-BDT	Gold tok+mor	-	-	-	-	-	-	-	82.1%	78.4%	75.2%	77.2%
Belarusian-HSE	Raw text	99.3%	69.0%	86.4%	77.9%	69.2%	63.0%	79.7%	66.1%	56.9%	34.7%	42.7%
Belarusian-HSE	Gold tok	-	-	87.2%	78.2%	69.6%	63.1%	80.2%	68.0%	58.8%	35.4%	44.0%
Belarusian-HSE	Gold tok+mor	-	-	-	-	-	-	-	79.4%	76.3%	71.9%	73.6%
Bulgarian-BTB	Raw text	99.9%	95.3%	97.6%	94.4%	95.4%	93.8%	94.6%	89.3%	85.2%	75.5%	74.1%
Bulgarian-BTB	Gold tok	-	-	97.8%	94.5%	95.5%	93.9%	94.7%	90.0%	85.9%	76.1%	74.7%
Bulgarian-BTB	Gold tok+mor	-	-	-	-	-	-	-	92.5%	89.1%	84.4%	84.7%
Catalan-AnCora	Raw text	100.0%	99.4%	98.0%	98.0%	97.4%	96.7%	97.9%	88.6%	85.6%	76.8%	77.2%
Catalan-AnCora	Gold tok	-	-	98.0%	98.0%	97.4%	96.7%	97.9%	88.7%	85.7%	76.8%	77.3%
Catalan-AnCora	Gold tok+mor	-	-	-	-	-	-	-	90.9%	88.6%	82.8%	83.3%
Chinese-GSD	Raw text	90.3%	98.8%	84.2%	84.0%	89.1%	82.8%	90.3%	62.8%	58.7%	49.0%	53.6%
Chinese-GSD	Gold tok	-	-	92.1%	91.9%	98.7%	90.7%	100.0%	75.6%	70.1%	59.6%	65.4%
Chinese-GSD	Gold tok+mor	-	-	-	-	-	-	-	84.8%	81.9%	75.9%	78.4%
Coptic-Scriptorium	Raw text	64.9%	29.7%	61.0%	60.4%	61.6%	59.9%	62.5%	36.6%	34.7%	23.2%	25.9%
Coptic-Scriptorium	Gold tok	-	-	93.1%	91.6%	95.1%	91.0%	94.4%	82.1%	76.8%	60.2%	63.4%
Coptic-Scriptorium	Gold tok+mor	-	-	-	-	-	-	-	86.2%	81.8%	70.1%	73.1%
Croatian-SET	Raw text	99.9%	94.9%	96.3%	-	84.5%	83.8%	94.8%	84.2%	78.4%	58.5%	69.9%
Croatian-SET	Gold tok	-	-	96.4%	-	84.6%	83.9%	94.9%	84.9%	79.0%	59.0%	70.5%
Croatian-SET	Gold tok+mor	-	-	-	-	-	-	-	88.0%	83.9%	79.3%	80.6%
Czech-CAC	Raw text	100.0%	99.7%	98.1%	90.7%	89.8%	89.5%	96.9%	86.0%	82.7%	70.0%	76.5%
Czech-CAC	Gold tok	-	-	98.1%	90.7%	89.8%	89.5%	96.9%	86.0%	82.7%	70.0%	76.6%
Czech-CAC	Gold tok+mor	-	-	-	-	-	-	-	89.6%	87.5%	84.6%	85.3%
Czech-CLTT	Raw text	99.4%	97.4%	96.5%	87.7%	87.8%	87.5%	96.0%	78.2%	74.7%	60.7%	68.5%
Czech-CLTT	Gold tok	-	-	97.2%	88.2%	88.4%	88.1%	96.5%	78.9%	75.5%	61.1%	68.8%
Czech-CLTT	Gold tok+mor	-	-	-	-	-	-	-	82.3%	79.4%	74.2%	75.0%
Czech-FicTree	Raw text	100.0%	98.4%	97.1%	90.0%	90.8%	89.6%	97.1%	86.1%	81.7%	68.2%	74.1%
Czech-FicTree	Gold tok	-	-	97.1%	90.0%	90.8%	89.6%	97.1%	86.2%	81.8%	68.3%	74.3%
Czech-FicTree	Gold tok+mor	-	-	-	-	-	-	-	90.5%	87.6%	83.2%	84.2%
Czech-PDT	Raw text	99.9%	93.6%	98.2%	92.8%	92.4%	91.9%	97.8%	87.1%	84.1%	74.5%	79.5%
Czech-PDT	Gold tok	-	-	98.3%	92.9%	92.5%	92.0%	97.9%	87.8%	84.8%	75.1%	80.2%
Czech-PDT	Gold tok+mor	-	-	-	-	-	-	-	90.2%	88.1%	85.5%	86.1%
Danish-DDT	Raw text	99.8%	91.6%	95.4%	-	94.8%	93.4%	94.7%	79.2%	75.9%	66.3%	66.8%
Danish-DDT	Gold tok	-	-	95.6%	-	95.0%	93.6%	94.9%	80.2%	76.8%	67.2%	67.5%
Danish-DDT	Gold tok+mor	-	-	-	-	-	-	-	84.8%	82.4%	77.4%	79.1%
Dutch-Alpino	Raw text	99.9%	91.7%	94.3%	91.5%	93.6%	90.8%	95.4%	82.3%	78.2%	63.0%	66.0%
Dutch-Alpino	Gold tok	-	-	94.4%	91.6%	93.6%	91.0%	95.5%	83.1%	78.9%	63.9%	66.9%
Dutch-Alpino	Gold tok+mor	-	-	-	-	-	-	-	86.6%	83.1%	75.1%	76.2%
Dutch-LassySmall	Raw text	99.7%	74.5%	94.1%	91.8%	93.7%	91.1%	95.5%	79.9%	75.9%	63.3%	64.3%
Dutch-LassySmall	Gold tok	-	-	94.3%	92.2%	94.2%	91.5%	95.9%	83.6%	79.1%	67.2%	68.3%
Dutch-LassySmall	Gold tok+mor	-	-	-	-	-	-	-	87.5%	84.1%	78.1%	78.8%
English-EWT	Raw text	99.1%	77.1%	93.5%	92.9%	94.5%	91.5%	96.0%	80.5%	77.5%	68.5%	71.0%
English-EWT	Gold tok	-	-	94.4%	93.9%	95.4%	92.5%	96.8%	84.5%	81.2%	72.0%	74.6%
English-EWT	Gold tok+mor	-	-	-	-	-	-	-	87.7%	85.8%	82.0%	82.7%
English-GUM	Raw text	99.7%	80.7%	93.2%	92.7%	93.9%	91.6%	94.4%	79.0%	74.7%	62.8%	62.7%
English-GUM	Gold tok	-	-	93.5%	93.1%	94.2%	92.0%	94.7%	81.2%	76.8%	64.6%	64.6%
English-GUM	Gold tok+mor	-	-	-	-	-	-	-	86.1%	83.8%	77.1%	78.2%
English-LinES	Raw text	99.9%	87.2%	94.6%	92.4%	94.8%	90.0%	95.9%	77.8%	72.7%	63.5%	64.8%
English-LinES	Gold tok	-	-	94.7%	92.5%	94.8%	90.0%	96.0%	78.3%	73.2%	64.0%	65.3%
English-LinES	Gold tok+mor	-	-	-	-	-	-	-	82.2%	78.3%	73.7%	75.8%
English-ParTUT	Raw text	99.5%	99.0%	93.9%	93.5%	93.5%	91.9%	96.4%	84.6%	80.8%	69.0%	71.1%
English-ParTUT	Gold tok	-	-	94.3%	93.9%	94.0%	92.3%	96.9%	85.1%	81.4%	69.5%	71.8%
English-ParTUT	Gold tok+mor	-	-	-	-	-	-	-	87.1%	85.6%	79.1%	80.2%
Estonian-EDT	Raw text	100.0%	91.7%	95.7%	96.8%	93.2%	91.6%	90.5%	79.5%	75.5%	67.7%	64.3%
Estonian-EDT	Gold tok	-	-	95.7%	96.9%	93.3%	91.7%	90.6%	80.3%	76.2%	68.3%	64.9%
Estonian-EDT	Gold tok+mor	-	-	-	-	-	-	-	85.1%	82.7%	79.5%	80.5%
Finnish-FTB	Raw text	99.9%	88.4%	92.4%	91.1%	92.8%	89.6%	88.6%	80.3%	76.0%	65.5%	62.0%
Finnish-FTB	Gold tok	-	-	92.6%	91.3%	93.0%	89.8%	88.8%	81.8%	77.4%	67.0%	63.4%
Finnish-FTB	Gold tok+mor	-	-	-	-	-	-	-	88.9%	86.7%	82.3%	83.3%
Finnish-TDT	Raw text	99.7%	89.8%	94.4%	95.6%	92.1%	90.8%	86.5%	80.8%	76.9%	68.8%	62.5%
Finnish-TDT	Gold tok	-	-	94.7%	95.9%	92.4%	91.0%	86.8%	81.9%	77.9%	69.5%	63.2%
Finnish-TDT	Gold tok+mor	-	-	-	-	-	-	-	86.4%	84.2%	81.3%	82.3%
French-GSD	Raw text	98.8%	94.1%	95.8%	-	95.5%	94.5%	96.6%	85.0%	81.8%	72.5%	74.4%
French-GSD	Gold tok	-	-	97.0%	-	96.6%	95.5%	97.8%	86.5%	83.4%	74.0%	75.5%
French-GSD	Gold tok+mor	-	-	-	-	-	-	-	89.0%	86.8%	82.3%	82.8%
French-ParTUT	Raw text	99.4%	100.0%	94.8%	94.3%	92.0%	91.0%	95.2%	89.0%	85.0%	68.0%	73.3%
French-ParTUT	Gold tok	-	-	95.4%	95.0%	92.6%	91.6%	95.8%	89.5%	85.8%	68.7%	73.7%
French-ParTUT	Gold tok+mor	-	-	-	-	-	-	-	91.6%	89.5%	82.4%	83.7%
French-Sequoia	Raw text	99.2%	88.6%	96.1%	-	95.2%	94.2%	97.0%	84.9%	82.1%	73.1%	75.4%
French-Sequoia	Gold tok	-	-	97.0%	-	96.0%	95.1%	97.8%	86.5%	83.8%	74.7%	76.6%
French-Sequoia	Gold tok+mor	-	-	-	-	-	-	-	89.4%	88.0%	83.8%	84.2%
French-Spoken	Raw text	99.9%	22.4%	92.9%	97.3%	-	90.5%	95.8%	72.2%	66.2%	54.2%	55.3%
French-Spoken	Gold tok	-	-	93.3%	97.3%	-	90.8%	95.9%	77.1%	70.8%	60.6%	61.4%
French-Spoken	Gold tok+mor	-	-	-	-	-	-	-	80.2%	75.3%	66.7%	68.0%
Galician-CTG	Raw text	99.2%	97.5%	96.3%	95.8%	99.0%	95.4%	96.2%	79.2%	76.2%	62.5%	65.4%
Galician-CTG	Gold tok	-	-	97.0%	96.5%	99.8%	96.2%	96.9%	80.8%	77.7%	64.3%	67.2%
Galician-CTG	Gold tok+mor	-	-	-	-	-	-	-	83.0%	80.7%	69.4%	74.1%
Galician-TreeGal	Raw text	98.7%	85.2%	91.0%	87.2%	89.6%	86.5%	92.5%	71.4%	65.8%	49.0%	51.4%
Galician-TreeGal	Gold tok	-	-	92.3%	88.3%	90.6%	87.5%	93.5%	74.2%	68.1%	51.7%	54.1%
Galician-TreeGal	Gold tok+mor	-	-	-	-	-	-	-	81.3%	76.9%	69.5%	70.6%
German-GSD	Raw text	99.6%	81.8%	91.4%	80.4%	69.9%	63.3%	95.4%	77.0%	71.7%	33.9%	60.4%
German-GSD	Gold tok	-	-	91.9%	80.8%	70.2%	63.7%	95.8%	79.7%	74.1%	35.2%	62.8%
German-GSD	Gold tok+mor	-	-	-	-	-	-	-	84.6%	80.3%	71.2%	74.5%
Gothic-PROIEL	Raw text	100.0%	28.9%	94.3%	94.9%	87.3%	85.3%	92.4%	69.1%	62.3%	48.8%	55.2%
Gothic-PROIEL	Gold tok	-	-	94.9%	95.3%	87.7%	86.0%	92.6%	78.3%	71.5%	57.4%	62.9%
Gothic-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	82.1%	77.8%	70.9%	74.4%
Greek-GDT	Raw text	99.8%	89.4%	95.8%	95.8%	90.3%	89.2%	94.7%	86.0%	82.8%	66.2%	69.5%
Greek-GDT	Gold tok	-	-	96.0%	96.0%	90.5%	89.4%	94.9%	86.7%	83.6%	67.0%	70.3%
Greek-GDT	Gold tok+mor	-	-	-	-	-	-	-	89.1%	87.3%	81.2%	82.1%
Hebrew-HTB	Raw text	85.0%	99.4%	80.5%	80.5%	78.7%	77.7%	81.5%	61.7%	58.3%	44.6%	47.4%
Hebrew-HTB	Gold tok	-	-	94.9%	94.9%	92.7%	91.5%	95.3%	83.6%	79.6%	64.3%	67.0%
Hebrew-HTB	Gold tok+mor	-	-	-	-	-	-	-	87.0%	84.9%	78.4%	78.8%
Hindi-HDTB	Raw text	100.0%	98.2%	95.8%	94.8%	90.3%	87.7%	98.0%	91.5%	87.3%	69.2%	80.3%
Hindi-HDTB	Gold tok	-	-	95.8%	94.8%	90.3%	87.7%	98.0%	91.7%	87.5%	69.3%	80.4%
Hindi-HDTB	Gold tok+mor	-	-	-	-	-	-	-	94.0%	91.0%	85.8%	87.0%
Hungarian-Szeged	Raw text	99.8%	95.6%	90.6%	-	88.1%	86.4%	88.5%	72.9%	67.2%	53.7%	57.9%
Hungarian-Szeged	Gold tok	-	-	90.7%	-	88.2%	86.5%	88.7%	73.3%	67.6%	53.9%	58.1%
Hungarian-Szeged	Gold tok+mor	-	-	-	-	-	-	-	80.5%	77.6%	72.7%	76.6%
Indonesian-GSD	Raw text	100.0%	94.1%	93.0%	92.2%	93.9%	87.1%	92.2%	81.0%	74.6%	63.6%	62.9%
Indonesian-GSD	Gold tok	-	-	93.0%	92.2%	93.9%	87.1%	92.2%	81.2%	74.8%	63.9%	63.2%
Indonesian-GSD	Gold tok+mor	-	-	-	-	-	-	-	84.0%	79.8%	76.4%	78.3%
Irish-IDT	Raw text	99.6%	95.9%	89.5%	88.2%	79.0%	75.3%	85.7%	74.0%	64.2%	38.2%	43.3%
Irish-IDT	Gold tok	-	-	89.8%	88.5%	79.4%	75.6%	86.1%	74.4%	64.4%	38.2%	43.2%
Irish-IDT	Gold tok+mor	-	-	-	-	-	-	-	78.9%	72.3%	60.7%	62.9%
Italian-ISDT	Raw text	99.7%	99.4%	97.0%	96.8%	97.1%	96.0%	97.2%	88.7%	86.1%	76.5%	76.5%
Italian-ISDT	Gold tok	-	-	97.2%	97.1%	97.3%	96.2%	97.5%	89.2%	86.6%	77.1%	77.1%
Italian-ISDT	Gold tok+mor	-	-	-	-	-	-	-	91.3%	89.8%	84.2%	84.6%
Italian-ParTUT	Raw text	99.7%	99.0%	96.6%	96.1%	96.2%	95.1%	96.3%	85.9%	83.2%	72.2%	71.2%
Italian-ParTUT	Gold tok	-	-	96.8%	96.3%	96.4%	95.2%	96.5%	85.9%	83.2%	72.0%	71.1%
Italian-ParTUT	Gold tok+mor	-	-	-	-	-	-	-	89.8%	87.8%	80.5%	81.2%
Italian-PoSTWITA	Raw text	99.4%	28.5%	94.0%	93.7%	94.5%	92.4%	94.9%	73.9%	68.8%	55.8%	56.5%
Italian-PoSTWITA	Gold tok	-	-	94.5%	94.1%	94.9%	92.8%	95.4%	80.7%	74.8%	63.7%	64.5%
Italian-PoSTWITA	Gold tok+mor	-	-	-	-	-	-	-	84.6%	79.8%	73.3%	74.0%
Japanese-GSD	Raw text	91.0%	95.0%	88.6%	88.1%	91.0%	88.1%	90.3%	75.3%	73.8%	60.8%	62.6%
Japanese-GSD	Gold tok	-	-	97.0%	96.3%	100.0%	96.3%	99.1%	92.8%	90.8%	81.0%	83.2%
Japanese-GSD	Gold tok+mor	-	-	-	-	-	-	-	95.0%	93.9%	87.2%	87.3%
Korean-GSD	Raw text	99.8%	94.8%	93.5%	81.8%	99.6%	79.5%	87.1%	69.6%	61.5%	54.2%	50.9%
Korean-GSD	Gold tok	-	-	93.7%	81.9%	99.7%	79.7%	87.2%	70.3%	62.1%	54.8%	51.4%
Korean-GSD	Gold tok+mor	-	-	-	-	-	-	-	72.5%	65.5%	60.4%	61.6%
Korean-Kaist	Raw text	99.9%	100.0%	93.3%	80.0%	-	80.0%	88.5%	77.7%	70.4%	61.8%	58.0%
Korean-Kaist	Gold tok	-	-	93.3%	80.1%	-	80.1%	88.5%	77.8%	70.5%	61.9%	58.0%
Korean-Kaist	Gold tok+mor	-	-	-	-	-	-	-	80.2%	73.7%	67.8%	68.3%
Latin-ITTB	Raw text	100.0%	91.3%	97.0%	92.7%	93.2%	91.0%	98.1%	82.8%	79.5%	70.0%	75.0%
Latin-ITTB	Gold tok	-	-	97.0%	92.7%	93.2%	91.0%	98.1%	83.8%	80.4%	70.4%	75.5%
Latin-ITTB	Gold tok+mor	-	-	-	-	-	-	-	88.5%	86.5%	82.7%	83.7%
Latin-PROIEL	Raw text	99.9%	35.9%	94.6%	94.7%	86.8%	85.7%	94.2%	66.3%	60.8%	48.1%	54.9%
Latin-PROIEL	Gold tok	-	-	94.9%	94.9%	87.2%	86.2%	94.3%	74.2%	68.3%	55.5%	62.0%
Latin-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	77.3%	73.4%	67.1%	70.4%
Latin-Perseus	Raw text	100.0%	98.5%	83.3%	67.2%	72.1%	67.2%	78.0%	57.1%	46.5%	29.4%	31.6%
Latin-Perseus	Gold tok	-	-	83.3%	67.2%	72.1%	67.2%	77.9%	57.1%	46.5%	29.4%	31.6%
Latin-Perseus	Gold tok+mor	-	-	-	-	-	-	-	67.5%	61.7%	56.1%	59.1%
Latvian-LVTB	Raw text	99.3%	98.2%	92.3%	83.0%	88.0%	82.5%	91.7%	76.2%	71.0%	57.8%	61.8%
Latvian-LVTB	Gold tok	-	-	92.9%	83.5%	88.6%	83.1%	92.3%	77.2%	71.9%	58.7%	62.7%
Latvian-LVTB	Gold tok+mor	-	-	-	-	-	-	-	84.9%	81.5%	77.3%	78.6%
Lithuanian-HSE	Raw text	98.8%	89.5%	73.7%	72.2%	68.5%	61.7%	72.5%	45.9%	33.8%	20.6%	23.3%
Lithuanian-HSE	Gold tok	-	-	74.2%	72.5%	69.2%	62.0%	73.1%	47.1%	34.6%	20.9%	23.2%
Lithuanian-HSE	Gold tok+mor	-	-	-	-	-	-	-	54.9%	47.7%	41.9%	44.2%
Maltese-MUDT	Raw text	99.8%	84.8%	94.1%	93.6%	-	93.6%	-	76.6%	71.0%	57.0%	60.6%
Maltese-MUDT	Gold tok	-	-	94.3%	93.8%	-	93.8%	-	77.7%	72.0%	57.9%	61.5%
Maltese-MUDT	Gold tok+mor	-	-	-	-	-	-	-	82.2%	77.9%	67.3%	69.0%
Marathi-UFAL	Raw text	90.1%	90.7%	71.3%	-	60.6%	58.1%	76.1%	60.3%	48.3%	24.7%	31.9%
Marathi-UFAL	Gold tok	-	-	77.7%	-	63.4%	60.4%	76.5%	68.0%	54.1%	26.6%	30.4%
Marathi-UFAL	Gold tok+mor	-	-	-	-	-	-	-	73.8%	63.6%	57.3%	59.8%
North Sami-Giella	Raw text	99.9%	98.8%	87.8%	89.4%	82.5%	78.4%	82.0%	64.7%	57.9%	46.7%	43.2%
North Sami-Giella	Gold tok	-	-	87.9%	89.6%	82.6%	78.5%	82.1%	64.9%	58.2%	46.9%	43.5%
North Sami-Giella	Gold tok+mor	-	-	-	-	-	-	-	81.4%	78.7%	74.2%	77.2%
Norwegian-Bokmaal	Raw text	99.8%	97.0%	96.5%	-	95.3%	94.1%	96.6%	86.5%	83.7%	74.8%	76.7%
Norwegian-Bokmaal	Gold tok	-	-	96.7%	-	95.5%	94.3%	96.8%	87.1%	84.3%	75.3%	77.2%
Norwegian-Bokmaal	Gold tok+mor	-	-	-	-	-	-	-	91.5%	89.6%	85.7%	86.6%
Norwegian-Nynorsk	Raw text	99.9%	93.3%	96.1%	-	94.9%	93.7%	96.4%	85.5%	82.3%	72.6%	74.4%
Norwegian-Nynorsk	Gold tok	-	-	96.3%	-	95.1%	93.8%	96.5%	86.2%	83.0%	73.4%	75.1%
Norwegian-Nynorsk	Gold tok+mor	-	-	-	-	-	-	-	91.1%	89.1%	85.1%	86.2%
Norwegian-NynorskLIA	Raw text	100.0%	99.9%	85.2%	-	86.5%	81.9%	92.7%	58.5%	49.8%	38.6%	42.1%
Norwegian-NynorskLIA	Gold tok	-	-	85.2%	-	86.5%	81.9%	92.7%	58.5%	49.8%	38.6%	42.1%
Norwegian-NynorskLIA	Gold tok+mor	-	-	-	-	-	-	-	74.1%	66.4%	59.1%	61.0%
Old Church Slavonic-PROIEL	Raw text	100.0%	40.4%	93.7%	93.7%	86.7%	85.3%	90.6%	73.1%	66.6%	55.1%	59.3%
Old Church Slavonic-PROIEL	Gold tok	-	-	94.0%	94.0%	87.1%	85.8%	90.8%	81.6%	74.8%	62.8%	66.3%
Old Church Slavonic-PROIEL	Gold tok+mor	-	-	-	-	-	-	-	86.6%	82.5%	77.0%	79.9%
Old French-SRCMF	Raw text	99.9%	100.0%	94.2%	93.8%	96.0%	93.3%	-	85.5%	79.3%	70.9%	74.6%
Old French-SRCMF	Gold tok	-	-	94.3%	93.9%	96.1%	93.4%	-	85.6%	79.4%	71.0%	74.7%
Old French-SRCMF	Gold tok+mor	-	-	-	-	-	-	-	88.8%	84.4%	78.4%	79.7%
Persian-Seraji	Raw text	99.7%	98.8%	96.0%	95.9%	96.1%	95.4%	93.6%	83.6%	79.6%	72.8%	70.1%
Persian-Seraji	Gold tok	-	-	96.3%	96.3%	96.4%	95.7%	93.9%	84.3%	80.2%	73.3%	70.5%
Persian-Seraji	Gold tok+mor	-	-	-	-	-	-	-	87.2%	84.3%	80.0%	80.8%
Polish-LFG	Raw text	99.8%	99.7%	96.7%	87.2%	89.1%	86.5%	94.5%	91.3%	87.9%	74.8%	78.9%
Polish-LFG	Gold tok	-	-	96.9%	87.3%	89.2%	86.7%	94.6%	91.6%	88.2%	75.1%	79.1%
Polish-LFG	Gold tok+mor	-	-	-	-	-	-	-	96.3%	95.0%	93.0%	93.2%
Polish-SZ	Raw text	99.9%	98.9%	95.5%	83.3%	83.5%	82.5%	93.3%	86.3%	82.2%	64.0%	72.3%
Polish-SZ	Gold tok	-	-	95.7%	83.5%	83.6%	82.7%	93.5%	86.9%	82.7%	64.5%	72.7%
Polish-SZ	Gold tok+mor	-	-	-	-	-	-	-	93.3%	91.6%	89.0%	89.6%
Portuguese-Bosque	Raw text	99.6%	90.0%	95.8%	-	94.5%	92.3%	96.6%	85.3%	82.2%	67.4%	72.1%
Portuguese-Bosque	Gold tok	-	-	96.3%	-	94.9%	92.7%	97.0%	86.4%	83.2%	68.2%	73.0%
Portuguese-Bosque	Gold tok+mor	-	-	-	-	-	-	-	87.8%	84.9%	77.8%	78.9%
Portuguese-GSD	Raw text	99.9%	97.0%	97.0%	97.0%	99.7%	97.0%	98.5%	88.0%	85.9%	77.9%	78.5%
Portuguese-GSD	Gold tok	-	-	97.2%	97.2%	99.9%	97.2%	98.7%	88.4%	86.3%	78.2%	78.8%
Portuguese-GSD	Gold tok+mor	-	-	-	-	-	-	-	90.9%	89.5%	83.7%	84.3%
Romanian-Nonstandard	Raw text	98.5%	96.6%	94.1%	89.1%	88.0%	86.8%	91.6%	82.0%	76.2%	57.9%	63.9%
Romanian-Nonstandard	Gold tok	-	-	95.5%	90.3%	89.3%	88.0%	92.9%	84.1%	78.2%	59.4%	65.4%
Romanian-Nonstandard	Gold tok+mor	-	-	-	-	-	-	-	86.1%	80.8%	72.4%	74.7%
Romanian-RRT	Raw text	99.7%	95.3%	96.7%	95.9%	96.1%	95.7%	96.6%	85.6%	80.2%	71.5%	71.8%
Romanian-RRT	Gold tok	-	-	96.9%	96.2%	96.4%	96.0%	96.8%	86.3%	81.0%	72.1%	72.5%
Romanian-RRT	Gold tok+mor	-	-	-	-	-	-	-	88.1%	83.3%	77.1%	78.1%
Russian-GSD	Raw text	99.9%	96.2%	94.4%	94.2%	84.3%	82.5%	74.9%	82.6%	77.3%	60.3%	47.5%
Russian-GSD	Gold tok	-	-	94.5%	94.3%	84.4%	82.6%	75.0%	83.0%	77.7%	60.5%	47.8%
Russian-GSD	Gold tok+mor	-	-	-	-	-	-	-	86.2%	83.3%	80.4%	81.2%
Russian-SynTagRus	Raw text	99.7%	98.8%	97.9%	-	93.6%	93.2%	96.6%	87.9%	85.3%	77.2%	79.7%
Russian-SynTagRus	Gold tok	-	-	98.2%	-	93.9%	93.5%	96.9%	88.5%	85.8%	77.6%	80.1%
Russian-SynTagRus	Gold tok+mor	-	-	-	-	-	-	-	90.3%	89.0%	86.9%	87.3%
Russian-Taiga	Raw text	98.0%	87.2%	86.4%	98.0%	75.8%	74.0%	82.7%	63.1%	54.9%	36.3%	39.0%
Russian-Taiga	Gold tok	-	-	88.1%	100.0%	77.5%	75.4%	84.3%	66.0%	57.2%	38.0%	40.9%
Russian-Taiga	Gold tok+mor	-	-	-	-	-	-	-	72.5%	67.2%	61.0%	62.8%
Serbian-SET	Raw text	100.0%	92.3%	96.8%	-	90.5%	90.3%	94.8%	86.4%	82.2%	69.6%	74.0%
Serbian-SET	Gold tok	-	-	96.9%	-	90.7%	90.4%	94.9%	87.0%	82.8%	70.3%	74.6%
Serbian-SET	Gold tok+mor	-	-	-	-	-	-	-	90.3%	86.9%	82.6%	84.5%
Slovak-SNK	Raw text	100.0%	85.3%	93.3%	77.1%	80.5%	75.1%	86.2%	80.0%	75.5%	54.6%	60.5%
Slovak-SNK	Gold tok	-	-	93.4%	77.2%	80.6%	75.2%	86.2%	81.5%	76.9%	55.6%	61.3%
Slovak-SNK	Gold tok+mor	-	-	-	-	-	-	-	89.2%	86.9%	84.0%	84.8%
Slovenian-SSJ	Raw text	98.3%	76.2%	94.5%	86.4%	86.6%	85.8%	93.7%	80.6%	77.4%	63.4%	69.0%
Slovenian-SSJ	Gold tok	-	-	96.2%	88.0%	88.4%	87.5%	95.3%	85.2%	81.8%	67.1%	72.9%
Slovenian-SSJ	Gold tok+mor	-	-	-	-	-	-	-	91.7%	90.2%	87.2%	87.6%
Slovenian-SST	Raw text	99.8%	23.1%	88.4%	80.2%	80.3%	77.7%	91.0%	53.9%	47.0%	34.4%	38.5%
Slovenian-SST	Gold tok	-	-	88.8%	80.7%	80.9%	78.3%	91.2%	64.7%	56.9%	43.1%	48.6%
Slovenian-SST	Gold tok+mor	-	-	-	-	-	-	-	74.8%	69.4%	63.7%	65.6%
Spanish-AnCora	Raw text	99.9%	99.0%	98.1%	98.1%	97.7%	96.9%	98.0%	87.6%	84.6%	76.3%	76.8%
Spanish-AnCora	Gold tok	-	-	98.2%	98.2%	97.8%	97.0%	98.1%	87.8%	84.8%	76.4%	76.9%
Spanish-AnCora	Gold tok+mor	-	-	-	-	-	-	-	90.2%	87.7%	81.8%	82.7%
Spanish-GSD	Raw text	99.8%	94.9%	95.5%	-	96.2%	93.7%	95.9%	85.3%	81.8%	68.8%	69.5%
Spanish-GSD	Gold tok	-	-	95.8%	-	96.4%	94.0%	96.2%	85.9%	82.3%	69.3%	70.0%
Spanish-GSD	Gold tok+mor	-	-	-	-	-	-	-	87.7%	85.1%	78.1%	79.0%
Swedish-LinES	Raw text	100.0%	86.8%	94.4%	91.8%	87.6%	84.4%	94.5%	79.8%	74.9%	59.6%	67.5%
Swedish-LinES	Gold tok	-	-	94.6%	91.9%	87.7%	84.5%	94.5%	80.5%	75.5%	60.1%	68.0%
Swedish-LinES	Gold tok+mor	-	-	-	-	-	-	-	84.7%	80.9%	77.5%	78.8%
Swedish-Talbanken	Raw text	99.9%	96.1%	95.6%	94.0%	94.5%	92.8%	95.5%	82.2%	78.2%	69.3%	70.3%
Swedish-Talbanken	Gold tok	-	-	95.8%	94.1%	94.7%	92.9%	95.6%	82.6%	78.7%	69.7%	70.7%
Swedish-Talbanken	Gold tok+mor	-	-	-	-	-	-	-	87.9%	85.1%	81.1%	82.2%
Tamil-TTB	Raw text	95.0%	100.0%	81.8%	76.9%	81.0%	76.1%	84.6%	60.0%	52.5%	42.2%	43.5%
Tamil-TTB	Gold tok	-	-	85.7%	80.1%	84.7%	79.3%	88.3%	65.0%	57.0%	46.3%	47.6%
Tamil-TTB	Gold tok+mor	-	-	-	-	-	-	-	78.4%	71.8%	67.2%	68.4%
Telugu-MTG	Raw text	99.8%	97.6%	90.5%	90.5%	98.7%	90.5%	-	87.7%	76.2%	65.6%	70.2%
Telugu-MTG	Gold tok	-	-	90.6%	90.6%	98.9%	90.6%	-	88.3%	76.8%	66.2%	70.8%
Telugu-MTG	Gold tok+mor	-	-	-	-	-	-	-	91.4%	82.2%	76.8%	77.1%
Turkish-IMST	Raw text	98.3%	96.4%	91.7%	90.7%	88.4%	86.1%	90.0%	61.5%	54.6%	44.8%	46.2%
Turkish-IMST	Gold tok	-	-	93.1%	92.1%	89.8%	87.4%	91.4%	64.1%	56.9%	46.1%	47.6%
Turkish-IMST	Gold tok+mor	-	-	-	-	-	-	-	65.6%	60.3%	55.1%	56.7%
Ukrainian-IU	Raw text	99.8%	97.2%	95.0%	84.1%	84.3%	83.3%	93.5%	79.9%	75.2%	57.8%	64.7%
Ukrainian-IU	Gold tok	-	-	95.2%	84.2%	84.4%	83.4%	93.7%	80.2%	75.6%	58.0%	65.0%
Ukrainian-IU	Gold tok+mor	-	-	-	-	-	-	-	85.0%	82.9%	78.8%	79.4%
Urdu-UDTB	Raw text	100.0%	98.3%	92.1%	89.9%	80.8%	76.2%	93.0%	84.1%	77.3%	50.5%	64.0%
Urdu-UDTB	Gold tok	-	-	92.2%	89.9%	80.8%	76.2%	93.0%	84.2%	77.4%	50.5%	64.0%
Urdu-UDTB	Gold tok+mor	-	-	-	-	-	-	-	87.8%	82.5%	74.3%	76.0%
Uyghur-UDT	Raw text	99.7%	82.9%	87.9%	90.0%	84.1%	76.3%	91.9%	70.8%	56.7%	37.4%	44.1%
Uyghur-UDT	Gold tok	-	-	88.2%	90.3%	84.4%	76.6%	92.2%	72.0%	57.9%	38.0%	44.9%
Uyghur-UDT	Gold tok+mor	-	-	-	-	-	-	-	74.4%	61.1%	50.3%	52.6%
Vietnamese-VTB	Raw text	85.4%	93.7%	76.2%	74.1%	85.1%	74.1%	84.7%	45.9%	40.8%	34.7%	36.8%
Vietnamese-VTB	Gold tok	-	-	87.6%	85.0%	99.5%	84.9%	98.9%	62.6%	54.5%	48.2%	50.8%
Vietnamese-VTB	Gold tok+mor	-	-	-	-	-	-	-	69.4%	66.3%	62.9%	65.2%

4. CoNLL18 Shared Task Baseline UD 2.2 Models

As part of CoNLL 2018 Shared Task in UD Parsing, baseline models for UDPipe were released. The CoNLL 2018 Shared Task models were trained on most of UD 2.2 treebanks (74 of them) and are distributed under the CC BY-NC-SA licence.

The models were released when the test set of UD 2.2 was unknown. Details about the concrete data split, hyperparameter values and model performance are available in the model archive.

4.1. Download

The CoNLL18 Shared Task Baseline UD 2.2 Models can be downloaded from LINDAT/CLARIN repository.

4.2. Acknowledgements

This work has been partially supported and has been using language resources and tools developed, stored and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).

The models were trained on a Universal Dependencies 2.2 treebanks.

5. Universal Dependencies 2.0 Models

Universal Dependencies 2.0 Models are distributed under the CC BY-NC-SA licence. The models are based solely on Universal Dependencies 2.0 treebanks. The models work in UDPipe version 1.2 and later.

Universal Dependencies 2.0 Models are versioned according to the date released in the format YYMMDD, where YY, MM and DD are two-digit representation of year, month and day, respectively. The latest version is 170801.

5.1. Download

The latest version 170801 of the Universal Dependencies 2.0 models can be downloaded from LINDAT/CLARIN repository.

5.2. Acknowledgements

This work has been partially supported and has been using language resources and tools developed, stored and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071). The wark was also partially supported by OP VVV projects CZ.02.1.01/0.0/0.0/16\_013/0001781 and CZ.02.2.69/0.0/0.0/16\_018/0002373, and by SVV project number 260 453.

The models were trained on Universal Dependencies 2.0 treebanks.

For the UD treebanks which do not contain original plain text version, raw text is used to train the tokenizer instead. The plain texts were taken from the W2C – Web to Corpus.

5.2.1. Publications

• (Straka et al. 2017) Milan Straka and Jana Straková. Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe. In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, Vancouver, Canada, August 2017.
• (Straka et al. 2016) Straka Milan, Hajič Jan, Straková Jana. UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), Portorož, Slovenia, May 2016.

5.3. Model Description

The Universal Dependencies 2.0 models contain 68 models of 50 languages, each consisting of a tokenizer, tagger, lemmatizer and dependency parser, all trained using the UD data. Note that we use custom train-dev split, by moving sentences from the beginning of dev data to the end of train data, until the training data is at least 9 times the dev data.

The tokenizer is trained using the SpaceAfter=No features. If the features are not present in the data, they can be filled in using raw text in the language in question.

The tagger, lemmatizer and parser are trained using gold UD data.

Details about model architecture and training process can be found in the (Straka et al. 2017) paper.

5.3.1. Reproducible Training

In case you want to train the same models, scripts for downloading and resplitting UD 2.0 data, precomputed word embedding, raw texts for tokenizers, all hyperparameter values and training scripts are available in the second archive on the model download page.

5.4. Model Performance

We present the tagger, lemmatizer and parser performance, measured on the testing portion of the data, evaluated in three different settings: using raw text only, using gold tokenization only, and using gold tokenization plus gold morphology (UPOS, XPOS, FEATS and Lemma).

Treebank	Mode	Words	Sents	UPOS	XPOS	Feats	AllTags	Lemma	UAS	LAS
Ancient Greek	Raw text	100.0%	98.7%	82.4%	72.3%	85.8%	72.3%	82.6%	64.4%	57.8%
Ancient Greek	Gold tok	-	-	82.4%	72.4%	85.8%	72.3%	82.7%	64.6%	57.9%
Ancient Greek	Gold tok+morph	-	-	-	-	-	-	-	69.2%	64.4%
Ancient Greek-PROIEL	Raw text	100.0%	47.2%	95.8%	96.0%	88.6%	87.2%	92.6%	71.8%	67.1%
Ancient Greek-PROIEL	Gold tok	-	-	95.8%	96.1%	88.7%	87.2%	92.8%	77.2%	72.3%
Ancient Greek-PROIEL	Gold tok+morph	-	-	-	-	-	-	-	79.7%	76.1%
Arabic	Raw text	93.8%	83.1%	88.4%	83.4%	83.5%	82.3%	87.5%	71.7%	65.8%
Arabic	Gold tok	-	-	94.4%	89.5%	89.6%	88.3%	92.6%	81.3%	74.3%
Arabic	Gold tok+morph	-	-	-	-	-	-	-	82.9%	77.9%
Basque	Raw text	100.0%	99.5%	93.2%	-	87.6%	-	93.8%	75.8%	70.7%
Basque	Gold tok	-	-	93.3%	-	87.7%	-	93.9%	75.9%	70.8%
Basque	Gold tok+morph	-	-	-	-	-	-	-	82.3%	78.4%
Belarusian	Raw text	99.4%	76.8%	88.2%	85.6%	71.7%	68.6%	81.3%	68.0%	60.6%
Belarusian	Gold tok	-	-	88.7%	85.7%	72.4%	69.2%	81.5%	69.4%	61.9%
Belarusian	Gold tok+morph	-	-	-	-	-	-	-	76.8%	74.0%
Bulgarian	Raw text	99.9%	93.9%	97.6%	94.6%	95.6%	94.0%	94.6%	88.8%	84.8%
Bulgarian	Gold tok	-	-	97.7%	94.7%	95.6%	94.1%	94.7%	89.5%	85.5%
Bulgarian	Gold tok+morph	-	-	-	-	-	-	-	92.6%	89.1%
Catalan	Raw text	100.0%	99.2%	98.0%	98.0%	97.1%	96.5%	97.9%	88.8%	85.7%
Catalan	Gold tok	-	-	98.0%	98.0%	97.2%	96.5%	97.9%	88.8%	85.8%
Catalan	Gold tok+morph	-	-	-	-	-	-	-	91.1%	88.7%
Chinese	Raw text	90.2%	98.8%	84.0%	83.8%	89.0%	82.7%	90.2%	62.9%	58.7%
Chinese	Gold tok	-	-	92.2%	92.0%	98.7%	90.8%	100.0%	75.6%	70.1%
Chinese	Gold tok+morph	-	-	-	-	-	-	-	84.1%	81.4%
Coptic	Raw text	65.8%	35.7%	62.6%	62.1%	65.7%	62.1%	64.6%	41.1%	39.3%
Coptic	Gold tok	-	-	95.1%	94.3%	99.7%	94.2%	96.2%	83.2%	79.2%
Coptic	Gold tok+morph	-	-	-	-	-	-	-	88.1%	84.9%
Croatian	Raw text	99.9%	97.0%	95.9%	-	84.3%	-	94.4%	83.6%	77.9%
Croatian	Gold tok	-	-	96.0%	-	84.4%	-	94.4%	83.9%	78.1%
Croatian	Gold tok+morph	-	-	-	-	-	-	-	87.1%	83.2%
Czech	Raw text	99.9%	91.6%	98.3%	92.8%	92.1%	91.7%	97.8%	86.8%	83.2%
Czech	Gold tok	-	-	98.4%	92.9%	92.2%	91.9%	97.9%	87.7%	84.1%
Czech	Gold tok+morph	-	-	-	-	-	-	-	90.2%	87.5%
Czech-CAC	Raw text	100.0%	99.8%	98.1%	90.6%	89.4%	89.1%	97.0%	86.9%	82.7%
Czech-CAC	Gold tok	-	-	98.1%	90.7%	89.5%	89.1%	97.1%	87.0%	82.8%
Czech-CAC	Gold tok+morph	-	-	-	-	-	-	-	89.7%	86.6%
Czech-CLTT	Raw text	99.5%	92.3%	96.5%	87.5%	87.8%	87.3%	96.8%	80.2%	76.6%
Czech-CLTT	Gold tok	-	-	97.0%	87.9%	88.3%	87.7%	97.2%	81.0%	77.6%
Czech-CLTT	Gold tok+morph	-	-	-	-	-	-	-	83.8%	80.8%
Danish	Raw text	99.8%	77.9%	95.2%	-	94.2%	-	94.9%	78.4%	74.7%
Danish	Gold tok	-	-	95.5%	-	94.5%	-	95.0%	80.4%	76.6%
Danish	Gold tok+morph	-	-	-	-	-	-	-	85.6%	82.7%
Dutch	Raw text	99.8%	77.6%	91.4%	88.1%	89.3%	87.0%	89.9%	75.4%	69.6%
Dutch	Gold tok	-	-	91.8%	88.8%	89.9%	87.7%	90.1%	77.0%	71.2%
Dutch	Gold tok+morph	-	-	-	-	-	-	-	82.9%	79.4%
Dutch-LassySmall	Raw text	100.0%	80.4%	97.6%	-	97.2%	-	98.1%	84.4%	82.0%
Dutch-LassySmall	Gold tok	-	-	97.7%	-	97.4%	-	98.2%	87.5%	85.0%
Dutch-LassySmall	Gold tok+morph	-	-	-	-	-	-	-	89.7%	87.4%
English	Raw text	99.0%	76.6%	93.5%	92.9%	94.4%	91.5%	96.0%	80.2%	77.2%
English	Gold tok	-	-	94.5%	93.9%	95.4%	92.5%	96.9%	84.3%	81.2%
English	Gold tok+morph	-	-	-	-	-	-	-	87.8%	86.0%
English-LinES	Raw text	99.9%	86.2%	95.0%	92.7%	-	-	-	78.6%	74.4%
English-LinES	Gold tok	-	-	95.1%	92.8%	-	-	-	79.5%	75.3%
English-LinES	Gold tok+morph	-	-	-	-	-	-	-	84.1%	81.1%
English-ParTUT	Raw text	99.6%	97.5%	94.2%	94.0%	93.3%	92.0%	96.9%	81.6%	77.9%
English-ParTUT	Gold tok	-	-	94.6%	94.4%	93.6%	92.3%	97.3%	82.1%	78.4%
English-ParTUT	Gold tok+morph	-	-	-	-	-	-	-	86.4%	84.5%
Estonian	Raw text	99.9%	94.2%	91.2%	93.2%	85.0%	83.2%	84.5%	72.4%	65.6%
Estonian	Gold tok	-	-	91.3%	93.2%	85.0%	83.3%	84.5%	72.8%	66.0%
Estonian	Gold tok+morph	-	-	-	-	-	-	-	83.1%	79.6%
Finnish	Raw text	99.7%	86.7%	94.5%	95.7%	91.5%	90.3%	86.5%	80.5%	76.9%
Finnish	Gold tok	-	-	94.9%	96.0%	91.8%	90.7%	86.8%	82.0%	78.4%
Finnish	Gold tok+morph	-	-	-	-	-	-	-	86.9%	84.7%
Finnish-FTB	Raw text	100.0%	86.4%	92.0%	91.0%	92.5%	89.2%	88.9%	80.1%	75.7%
Finnish-FTB	Gold tok	-	-	92.2%	91.3%	92.7%	89.5%	88.9%	81.7%	77.3%
Finnish-FTB	Gold tok+morph	-	-	-	-	-	-	-	88.8%	86.5%
French	Raw text	98.9%	94.6%	95.4%	-	95.5%	-	96.6%	84.2%	80.7%
French	Gold tok	-	-	96.5%	-	96.5%	-	97.6%	85.4%	82.0%
French	Gold tok+morph	-	-	-	-	-	-	-	88.4%	86.0%
French-ParTUT	Raw text	99.0%	97.8%	94.5%	94.2%	91.9%	90.8%	94.3%	82.9%	78.7%
French-ParTUT	Gold tok	-	-	95.6%	95.3%	92.7%	91.6%	95.2%	84.1%	80.2%
French-ParTUT	Gold tok+morph	-	-	-	-	-	-	-	88.1%	85.3%
French-Sequoia	Raw text	99.1%	84.0%	95.9%	-	95.1%	-	96.8%	83.2%	80.6%
French-Sequoia	Gold tok	-	-	96.8%	-	96.0%	-	97.7%	85.1%	82.7%
French-Sequoia	Gold tok+morph	-	-	-	-	-	-	-	88.7%	87.4%
Galician	Raw text	99.9%	95.8%	97.2%	96.7%	99.7%	96.4%	97.1%	81.0%	77.8%
Galician	Gold tok	-	-	97.2%	96.8%	99.8%	96.4%	97.1%	81.2%	77.9%
Galician	Gold tok+morph	-	-	-	-	-	-	-	83.1%	80.5%
Galician-TreeGal	Raw text	98.7%	86.7%	91.1%	87.8%	89.9%	87.0%	92.6%	71.5%	66.3%
Galician-TreeGal	Gold tok	-	-	92.4%	88.8%	91.0%	88.0%	93.7%	74.4%	68.7%
Galician-TreeGal	Gold tok+morph	-	-	-	-	-	-	-	81.5%	77.1%
German	Raw text	99.7%	79.3%	90.7%	94.7%	80.5%	76.3%	95.4%	74.0%	68.6%
German	Gold tok	-	-	91.2%	95.0%	80.9%	76.7%	95.6%	76.5%	70.7%
German	Gold tok+morph	-	-	-	-	-	-	-	84.7%	82.2%
Gothic	Raw text	100.0%	29.5%	94.2%	94.8%	87.6%	85.6%	92.9%	69.7%	63.5%
Gothic	Gold tok	-	-	94.8%	95.3%	88.0%	86.5%	92.9%	78.8%	72.6%
Gothic	Gold tok+morph	-	-	-	-	-	-	-	82.2%	78.3%
Greek	Raw text	99.9%	88.2%	95.8%	95.8%	90.3%	89.1%	94.5%	84.2%	80.4%
Greek	Gold tok	-	-	96.0%	96.0%	90.5%	89.3%	94.6%	85.0%	81.1%
Greek	Gold tok+morph	-	-	-	-	-	-	-	87.9%	85.9%
Hebrew	Raw text	85.2%	100.0%	80.9%	80.9%	77.6%	76.8%	79.6%	62.2%	57.9%
Hebrew	Gold tok	-	-	95.1%	95.1%	91.3%	90.5%	93.2%	84.5%	78.9%
Hebrew	Gold tok+morph	-	-	-	-	-	-	-	87.8%	84.3%
Hindi	Raw text	100.0%	99.1%	95.8%	94.9%	90.3%	87.7%	98.0%	91.3%	87.3%
Hindi	Gold tok	-	-	95.8%	94.9%	90.3%	87.7%	98.0%	91.4%	87.3%
Hindi	Gold tok+morph	-	-	-	-	-	-	-	93.9%	91.0%
Hungarian	Raw text	99.8%	96.2%	91.6%	-	70.5%	-	89.3%	74.1%	68.1%
Hungarian	Gold tok	-	-	91.8%	-	70.6%	-	89.5%	74.5%	68.5%
Hungarian	Gold tok+morph	-	-	-	-	-	-	-	81.2%	78.5%
Indonesian	Raw text	100.0%	92.0%	93.5%	-	99.5%	-	-	80.6%	74.3%
Indonesian	Gold tok	-	-	93.5%	-	99.6%	-	-	80.8%	74.5%
Indonesian	Gold tok+morph	-	-	-	-	-	-	-	83.1%	79.1%
Irish	Raw text	99.4%	94.3%	88.0%	86.9%	75.1%	72.7%	85.5%	72.5%	62.4%
Irish	Gold tok	-	-	88.5%	87.4%	75.5%	73.1%	86.0%	73.3%	63.1%
Irish	Gold tok+morph	-	-	-	-	-	-	-	78.1%	71.4%
Italian	Raw text	99.8%	97.1%	97.2%	97.0%	97.0%	96.1%	97.3%	88.8%	86.1%
Italian	Gold tok	-	-	97.4%	97.2%	97.2%	96.3%	97.5%	89.3%	86.6%
Italian	Gold tok+morph	-	-	-	-	-	-	-	91.3%	89.7%
Japanese	Raw text	91.9%	95.1%	89.1%	-	91.8%	-	91.1%	78.0%	76.6%
Japanese	Gold tok	-	-	96.6%	-	100.0%	-	99.0%	93.4%	91.5%
Japanese	Gold tok+morph	-	-	-	-	-	-	-	95.6%	95.0%
Kazakh	Raw text	94.0%	84.9%	52.0%	52.1%	47.2%	40.0%	59.2%	40.2%	23.9%
Kazakh	Gold tok	-	-	55.4%	55.4%	50.1%	42.2%	63.1%	45.2%	27.0%
Kazakh	Gold tok+morph	-	-	-	-	-	-	-	60.5%	42.5%
Korean	Raw text	99.7%	92.7%	94.4%	89.7%	99.3%	89.7%	99.4%	67.4%	60.5%
Korean	Gold tok	-	-	94.7%	90.0%	99.6%	90.0%	99.7%	68.4%	61.5%
Korean	Gold tok+morph	-	-	-	-	-	-	-	71.7%	65.8%
Latin	Raw text	100.0%	98.0%	83.4%	67.6%	72.5%	67.6%	51.2%	56.5%	46.0%
Latin	Gold tok	-	-	83.4%	67.6%	72.5%	67.6%	51.2%	56.6%	46.1%
Latin	Gold tok+morph	-	-	-	-	-	-	-	67.8%	61.5%
Latin-ITTB	Raw text	99.9%	82.5%	97.2%	92.7%	93.5%	91.3%	97.8%	79.7%	76.0%
Latin-ITTB	Gold tok	-	-	97.3%	92.8%	93.6%	91.4%	97.9%	81.8%	78.1%
Latin-ITTB	Gold tok+morph	-	-	-	-	-	-	-	87.6%	85.2%
Latin-PROIEL	Raw text	99.9%	31.0%	94.9%	95.0%	87.7%	86.7%	94.8%	66.1%	60.7%
Latin-PROIEL	Gold tok	-	-	95.2%	95.2%	88.4%	87.4%	95.0%	75.3%	69.4%
Latin-PROIEL	Gold tok+morph	-	-	-	-	-	-	-	79.0%	75.0%
Latvian	Raw text	99.2%	97.1%	89.6%	76.2%	83.2%	75.7%	87.6%	69.2%	62.8%
Latvian	Gold tok	-	-	90.2%	76.8%	84.0%	76.3%	88.3%	70.3%	63.9%
Latvian	Gold tok+morph	-	-	-	-	-	-	-	78.7%	74.9%
Lithuanian	Raw text	98.2%	92.0%	74.0%	73.0%	68.9%	63.7%	73.5%	44.0%	32.4%
Lithuanian	Gold tok	-	-	74.6%	73.5%	69.7%	64.2%	74.2%	44.6%	33.0%
Lithuanian	Gold tok+morph	-	-	-	-	-	-	-	55.6%	46.5%
Norwegian-Bokmaal	Raw text	99.8%	96.5%	96.9%	-	95.3%	-	96.6%	86.9%	84.1%
Norwegian-Bokmaal	Gold tok	-	-	97.1%	-	95.5%	-	96.8%	87.5%	84.7%
Norwegian-Bokmaal	Gold tok+morph	-	-	-	-	-	-	-	91.7%	89.6%
Norwegian-Nynorsk	Raw text	99.9%	92.2%	96.5%	-	94.9%	-	96.4%	85.6%	82.5%
Norwegian-Nynorsk	Gold tok	-	-	96.6%	-	95.0%	-	96.5%	86.5%	83.3%
Norwegian-Nynorsk	Gold tok+morph	-	-	-	-	-	-	-	91.0%	88.6%
Old Church Slavonic	Raw text	100.0%	40.5%	93.8%	93.8%	86.9%	85.7%	91.2%	73.6%	66.9%
Old Church Slavonic	Gold tok	-	-	94.1%	94.1%	87.6%	86.5%	91.2%	81.6%	74.7%
Old Church Slavonic	Gold tok+morph	-	-	-	-	-	-	-	86.7%	82.2%
Persian	Raw text	99.7%	98.2%	96.0%	96.0%	96.1%	95.4%	93.5%	83.3%	79.4%
Persian	Gold tok	-	-	96.4%	96.3%	96.4%	95.7%	93.8%	83.8%	80.0%
Persian	Gold tok+morph	-	-	-	-	-	-	-	87.7%	84.9%
Polish	Raw text	99.9%	99.7%	95.6%	84.0%	84.1%	83.1%	93.4%	86.7%	80.7%
Polish	Gold tok	-	-	95.7%	84.1%	84.2%	83.3%	93.6%	87.0%	81.0%
Polish	Gold tok+morph	-	-	-	-	-	-	-	92.9%	89.5%
Portuguese	Raw text	99.6%	89.4%	96.4%	72.7%	93.3%	71.6%	96.8%	86.0%	82.6%
Portuguese	Gold tok	-	-	96.8%	73.0%	93.7%	71.9%	97.2%	87.2%	83.6%
Portuguese	Gold tok+morph	-	-	-	-	-	-	-	89.6%	87.5%
Portuguese-BR	Raw text	99.9%	96.8%	97.0%	97.0%	99.7%	97.0%	98.8%	88.5%	86.3%
Portuguese-BR	Gold tok	-	-	97.2%	97.2%	99.9%	97.2%	98.9%	88.8%	86.6%
Portuguese-BR	Gold tok+morph	-	-	-	-	-	-	-	90.5%	89.1%
Romanian	Raw text	99.7%	93.9%	96.6%	95.9%	96.0%	95.7%	96.5%	85.6%	80.2%
Romanian	Gold tok	-	-	96.9%	96.2%	96.3%	96.0%	96.8%	86.2%	80.8%
Romanian	Gold tok+morph	-	-	-	-	-	-	-	87.8%	83.0%
Russian	Raw text	99.9%	96.9%	94.7%	94.4%	84.4%	82.8%	75.0%	80.3%	75.5%
Russian	Gold tok	-	-	94.8%	94.5%	84.5%	82.9%	75.1%	80.8%	76.0%
Russian	Gold tok+morph	-	-	-	-	-	-	-	84.8%	81.9%
Russian-SynTagRus	Raw text	99.6%	98.0%	98.0%	-	93.6%	-	95.6%	89.8%	87.2%
Russian-SynTagRus	Gold tok	-	-	98.4%	-	93.9%	-	95.9%	90.4%	87.9%
Russian-SynTagRus	Gold tok+morph	-	-	-	-	-	-	-	91.8%	90.5%
Sanskrit	Raw text	88.1%	29.0%	52.0%	-	35.2%	-	50.2%	38.8%	22.5%
Sanskrit	Gold tok	-	-	57.6%	-	43.6%	-	60.6%	58.5%	34.3%
Sanskrit	Gold tok+morph	-	-	-	-	-	-	-	72.9%	58.5%
Slovak	Raw text	100.0%	83.5%	93.2%	77.5%	79.7%	77.1%	85.9%	80.4%	75.2%
Slovak	Gold tok	-	-	93.3%	77.6%	79.9%	77.2%	86.0%	82.0%	76.9%
Slovak	Gold tok+morph	-	-	-	-	-	-	-	88.2%	85.5%
Slovenian	Raw text	99.9%	98.9%	96.2%	88.2%	88.5%	87.7%	95.3%	84.9%	81.6%
Slovenian	Gold tok	-	-	96.2%	88.2%	88.6%	87.7%	95.4%	85.0%	81.7%
Slovenian	Gold tok+morph	-	-	-	-	-	-	-	91.8%	90.5%
Slovenian-SST	Raw text	99.9%	17.8%	89.0%	81.1%	81.3%	78.6%	91.6%	53.0%	46.6%
Slovenian-SST	Gold tok	-	-	89.4%	81.6%	81.8%	79.3%	91.7%	63.4%	56.0%
Slovenian-SST	Gold tok+morph	-	-	-	-	-	-	-	75.5%	70.6%
Spanish	Raw text	99.7%	95.3%	95.5%	-	96.1%	-	95.9%	84.9%	81.4%
Spanish	Gold tok	-	-	95.8%	-	96.3%	-	96.1%	85.5%	81.9%
Spanish	Gold tok+morph	-	-	-	-	-	-	-	88.0%	85.3%
Spanish-AnCora	Raw text	99.9%	98.0%	98.1%	98.1%	97.5%	96.8%	98.1%	87.7%	84.5%
Spanish-AnCora	Gold tok	-	-	98.2%	98.2%	97.5%	96.9%	98.1%	87.8%	84.7%
Spanish-AnCora	Gold tok+morph	-	-	-	-	-	-	-	90.2%	87.6%
Swedish	Raw text	99.8%	94.6%	95.6%	93.9%	94.4%	92.8%	95.5%	81.4%	77.8%
Swedish	Gold tok	-	-	95.8%	94.1%	94.6%	93.1%	95.7%	82.1%	78.4%
Swedish	Gold tok+morph	-	-	-	-	-	-	-	88.0%	85.0%
Swedish-LinES	Raw text	100.0%	85.7%	94.8%	92.2%	-	-	-	80.4%	75.7%
Swedish-LinES	Gold tok	-	-	94.8%	92.3%	-	-	-	81.3%	76.6%
Swedish-LinES	Gold tok+morph	-	-	-	-	-	-	-	86.0%	82.6%
Tamil	Raw text	95.3%	89.2%	82.2%	77.7%	80.9%	77.2%	85.3%	59.5%	52.0%
Tamil	Gold tok	-	-	85.8%	81.0%	84.2%	80.3%	89.1%	64.9%	56.5%
Tamil	Gold tok+morph	-	-	-	-	-	-	-	78.9%	71.8%
Turkish	Raw text	98.1%	96.8%	92.4%	91.5%	87.3%	85.5%	90.2%	62.9%	55.8%
Turkish	Gold tok	-	-	94.0%	93.0%	88.9%	87.0%	91.7%	65.5%	58.0%
Turkish	Gold tok+morph	-	-	-	-	-	-	-	66.8%	61.1%
Ukrainian	Raw text	99.8%	95.1%	88.5%	70.7%	70.9%	67.6%	86.7%	69.9%	61.5%
Ukrainian	Gold tok	-	-	88.6%	70.8%	71.0%	67.7%	86.9%	70.2%	61.8%
Ukrainian	Gold tok+morph	-	-	-	-	-	-	-	79.0%	74.5%
Urdu	Raw text	100.0%	98.3%	92.4%	90.5%	80.6%	76.3%	93.0%	84.6%	77.6%
Urdu	Gold tok	-	-	92.4%	90.5%	80.7%	76.3%	93.0%	84.7%	77.7%
Urdu	Gold tok+morph	-	-	-	-	-	-	-	88.2%	83.0%
Uyghur	Raw text	99.8%	67.2%	74.7%	79.1%	-	-	-	55.1%	35.0%
Uyghur	Gold tok	-	-	75.1%	79.3%	-	-	-	56.5%	35.8%
Uyghur	Gold tok+morph	-	-	-	-	-	-	-	62.3%	42.0%
Vietnamese	Raw text	85.3%	92.9%	77.4%	75.4%	85.1%	75.4%	84.5%	46.9%	42.5%
Vietnamese	Gold tok	-	-	89.3%	86.8%	99.6%	86.8%	99.0%	64.4%	57.2%
Vietnamese	Gold tok+morph	-	-	-	-	-	-	-	70.7%	67.9%

6. CoNLL17 Shared Task Baseline UD 2.0 Models

As part of CoNLL 2017 Shared Task in UD Parsing, baseline models for UDPipe were released. The CoNLL 2017 Shared Task models were trained on most of UD 2.0 treebanks (64 of them) and are distributed under the CC BY-NC-SA licence.

Note that the models were released when the test set of UD 2.0 was unknown. Therefore, the models were trained on a subset of training data only, to allow fair comparison on the development data (which were unused during training and hyperparameter settings). Consequently, the performance of the models is not directly comparable to other models. Details about the concrete data split, hyperparameter values and model performance are available in the model archive.

6.1. Download

The CoNLL17 Shared Task Baseline UD 2.0 Models can be downloaded from LINDAT/CLARIN repository.

6.2. Acknowledgements

This work has been partially supported and has been using language resources and tools developed, stored and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).

The models were trained on a Universal Dependencies 2.0 treebanks.

7. Universal Dependencies 1.2 Models

Universal Dependencies 1.2 Models are distributed under the CC BY-NC-SA licence. The models are based solely on Universal Dependencies 1.2 treebanks. The models work in UDPipe version 1.0.

Universal Dependencies 1.2 Models are versioned according to the date released in the format YYMMDD, where YY, MM and DD are two-digit representation of year, month and day, respectively. The latest version is 160523.

7.1. Download

The latest version 160523 of the Universal Dependencies 1.2 models can be downloaded from LINDAT/CLARIN repository.

7.2. Acknowledgements

This work has been partially supported and has been using language resources and tools developed, stored and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).

The models were trained on Universal Dependencies 1.2 treebanks.

For the UD treebanks which do not contain original plain text version, raw text is used to train the tokenizer instead. The plain texts were taken from the W2C – Web to Corpus.

7.2.1. Publications

• (Straka et al. 2016) Straka Milan, Hajič Jan, Straková Jana. UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing. LREC 2016, Portorož, Slovenia, May 2016.

7.3. Model Description

The Universal Dependencies 1.2 models contain 36 models, each consisting of a tokenizer, tagger, lemmatizer and dependency parser, all trained using the UD data. The model for Japanese is missing, because we do not have the license for the required corpus of Mainichi Shinbun 1995.

The tokenizer is trained using the SpaceAfter=No features. If the features are not present in the data, they can be filled in using raw text in the language in question (surprisingly, quite little data suffices, we use 500kB).

The tagger, lemmatizer and parser are trained using gold UD data.

Details about model architecture and training process can be found in the (Straka et al. 2016) paper.

7.4. Model Performance

We present the tagger, lemmatizer and parser performance, measured on the testing portion of the data. Only the segmentation and the tokenization of the testing data is retained before evaluation. Therefore, the dependency parser is evaluated without gold POS tags.

Treebank	UPOS	XPOS	Feats	All Tags	Lemma	UAS	LAS
Ancient Greek	91.1%	77.8%	88.7%	77.7%	86.9%	68.1%	61.6%
Ancient Greek-PROIEL	96.7%	96.4%	89.3%	88.4%	93.4%	75.8%	69.6%
Arabic	98.8%	97.7%	97.8%	97.6%	-	80.4%	75.6%
Basque	93.3%	-	87.2%	85.4%	93.5%	74.8%	69.5%
Bulgarian	97.8%	94.8%	94.4%	93.1%	94.6%	89.0%	84.2%
Croatian	94.9%	-	85.5%	85.0%	93.1%	78.6%	71.0%
Czech	98.4%	93.2%	92.6%	92.2%	97.8%	86.9%	83.0%
Danish	95.8%	-	94.8%	93.6%	95.2%	78.6%	74.8%
Dutch	89.7%	88.7%	91.2%	86.4%	88.9%	78.1%	70.7%
English	94.5%	93.8%	95.4%	92.5%	97.0%	84.2%	80.6%
Estonian	88.0%	73.7%	80.0%	73.6%	77.0%	79.9%	71.5%
Finnish	94.9%	96.0%	93.2%	92.1%	86.8%	81.0%	76.5%
Finnish-FTB	94.0%	91.6%	93.3%	91.2%	89.1%	81.5%	76.9%
French	95.8%	-	-	95.8%	-	82.8%	78.4%
German	90.5%	-	-	90.5%	-	78.2%	72.2%
Gothic	95.5%	95.7%	88.0%	86.3%	93.4%	76.4%	68.2%
Greek	97.3%	97.3%	92.8%	91.7%	94.8%	80.3%	76.5%
Hebrew	94.9%	94.9%	91.3%	90.5%	-	82.6%	76.8%
Hindi	95.8%	94.8%	90.2%	87.7%	98.0%	91.7%	87.5%
Hungarian	92.6%	-	89.9%	88.9%	86.9%	77.0%	70.6%
Indonesian	93.5%	-	-	93.5%	-	79.9%	73.3%
Irish	91.8%	90.3%	79.4%	76.6%	87.3%	74.4%	66.1%
Italian	97.2%	97.0%	97.1%	96.2%	97.7%	88.6%	85.8%
Latin	91.2%	75.8%	79.3%	75.6%	79.9%	57.1%	46.7%
Latin-ITT	98.8%	94.0%	94.6%	93.8%	98.3%	79.9%	76.4%
Latin-PROIEL	96.4%	96.0%	88.9%	88.2%	95.3%	75.3%	68.3%
Norwegian	97.2%	-	95.5%	94.7%	96.9%	86.7%	84.1%
Old Church Slavonic	95.3%	95.1%	89.1%	88.2%	92.9%	80.6%	73.4%
Persian	97.0%	96.3%	96.5%	96.2%	-	83.8%	79.4%
Polish	95.8%	84.0%	84.1%	83.8%	92.8%	86.3%	79.6%
Portuguese	97.6%	92.3%	95.3%	92.0%	97.8%	85.8%	81.9%
Romanian	89.0%	81.0%	82.3%	81.0%	75.3%	68.6%	56.9%
Slovenian	95.7%	88.2%	88.6%	87.5%	95.0%	84.1%	80.3%
Spanish	95.3%	-	95.9%	93.4%	96.3%	84.2%	80.3%
Swedish	95.8%	93.9%	94.8%	93.2%	95.5%	81.4%	77.1%
Tamil	85.9%	80.8%	84.3%	80.2%	88.0%	67.2%	58.8%