CzEng 1.0 is the fourth release of a sentence-parallel Czech-English corpus compiled at the Institute of Formal and Applied Linguistics (ÚFAL) freely available for non-commercial research purposes.
CzEng 1.0 contains 15 million parallel sentences (233 million English and 206 million Czech tokens) from seven different types of sources automatically annotated at surface and deep (a- and t-) layers of syntactic representation. and EuroMatrix Plus (FP7-ICT-2007-3-231720 of the EU and 7E09003+7E11051 of the Ministry of Education, Youth and Sports of the Czech Republic),
Faust (FP7-ICT-2009-4-247762 of the EU and 7E11041 of the Ministry of Education, Youth and Sports of the Czech Republic),
GAČR P406/10/P259,
GAUK 116310,
GAUK 4226/2011
This corpus contains the text of De Latinae Linguae Reparatione authored by Marcus Antonius Sabellicus (1436–1506), annotated with respect to lemmas, part-of-speech tags, morphological features and syntactic dependencies according to the typological formalism of Universal Dependencies (UD).
The Sequoia corpus is a set of 3,099 linguistically-annotated French sentences, originating from four sources (Europarl, European Agency Reports, French regional journal L'Est Républicain, and French wikipedia).
Several types of annotations were added over the years.
The current release comprises:
- parts-of-speech (SEQUOIA ANR-08-EMER-013 project)
- syntactic dependency trees
- deep syntactic dependency graphs (Deep sequoia project)
- multi-word expressions and named entities (PARSEME COST project and PARSEME-FR ANR-14-CERA-0001 project)
- coarse semantic tags for nouns (FrSemCor project)
See the deep sequoia page for a detailed description: https://deep-sequoia.inria.fr/
Syntactic (including deep-syntactic - tectogrammatical) annotation of user-generated noisy sentences. The annotation was made on Czech-English and English-Czech Faust Dev/Test sets.
The English data includes manual annotations of English reference translations of Czech source texts. This texts were translated independently by two translators. After some necessary cleanings, 1000 segments were randomly selected for manual annotation. Both the reference translations were annotated, which means 2000 annotated segments in total.
The Czech data includes manual annotations of Czech reference translations of English source texts. This texts were translated independently by three translators. After some necessary cleanings, 1000 segments were randomly selected for manual annotation. All three reference translations were annotated, which means 3000 annotated segments in total.
Faust is part of PDT-C 1.0 (http://hdl.handle.net/11234/1-3185).
FicTree is a dependency treebank of Czech fiction manually annotated in the format of the analytical layer of the Prague Dependency Trebank. The treebank consists of 12,760 sentences (166,432 tokens). The texts come from eight literary works published in the Czech Republic between 1991 and 2007. The syntactic annotation of the treebank was first performed by two distinct parsers (MSTParser and MaltParser) trained on the PDT training data, then manually corrected. Any differences between the two versions were resolved manually (by another annotator).
The corpus is provided in a vertical format, where sentence boundaries are marked with a blank line. Every word form is written on a separate line, followed by five tab-separated attributes: lemma, tag, ID (word index in the sentence), head and deprel (analytical function, afun in the PDT formalism). The texts are shuffled in random chunks of maximum 100 words (respecting sentence boundaries). Each chunk is provided as a separate file, with the suggested division into train, dev and test sets written as file prefix.
HamleDT 2.0 is a collection of 30 existing treebanks harmonized into a common annotation style, the Prague Dependencies, and further transformed into Stanford Dependencies, a treebank annotation style that became popular recently. We use the newest basic Universal Stanford Dependencies, without added language-specific subtypes.
HamleDT (HArmonized Multi-LanguagE Dependency Treebank) is a compilation of existing dependency treebanks (or dependency conversions of other treebanks), transformed so that they all conform to the same annotation style. This version uses Universal Dependencies as the common annotation style.
Update (November 1017): for a current collection of harmonized dependency treebanks, we recommend using the Universal Dependencies (UD). All of the corpora that are distributed in HamleDT in full are also part of the UD project; only some corpora from the Patch group (where HamleDT provides only the harmonizing scripts but not the full corpus data) are available in HamleDT but not in UD.
This package contains data used in the IWPT 2020 shared task. It contains training, development and test (evaluation) datasets. The data is based on a subset of Universal Dependencies release 2.5 (http://hdl.handle.net/11234/1-3105) but some treebanks contain additional enhanced annotations. Moreover, not all of these additions became part of Universal Dependencies release 2.6 (http://hdl.handle.net/11234/1-3226), which makes the shared task data unique and worth a separate release to enable later comparison with new parsing algorithms. The package also contains a number of Perl and Python scripts that have been used to process the data during preparation and during the shared task. Finally, the package includes the official primary submission of each team participating in the shared task.
This package contains data used in the IWPT 2021 shared task. It contains training, development and test (evaluation) datasets. The data is based on a subset of Universal Dependencies release 2.7 (http://hdl.handle.net/11234/1-3424) but some treebanks contain additional enhanced annotations. Moreover, not all of these additions became part of Universal Dependencies release 2.8 (http://hdl.handle.net/11234/1-3687), which makes the shared task data unique and worth a separate release to enable later comparison with new parsing algorithms. The package also contains a number of Perl and Python scripts that have been used to process the data during preparation and during the shared task. Finally, the package includes the official primary submission of each team participating in the shared task.
Netgraph is a graphically oriented client-server application for searching in linguistically annotated treebanks. The query language of Netgraph is simple and intuitive, yet powerful enough for treebanks with complex annotations schemes. The primary purpose of Netgraph is searching in the Prague Dependency Treebank 2.0, nevertheless it can be used for other treebanks as well.