CoNLL 2017 and 2018 shared tasks:
Multilingual Parsing from Raw Text to Universal Dependencies
This package contains the test data in the form in which they ware presented
to the participating systems: raw text files and files preprocessed by UDPipe.
The metadata.json files contain lists of files to process and to output;
README files in the respective folders describe the syntax of metadata.json.
For full training, development and gold standard test data, see
Universal Dependencies 2.0 (CoNLL 2017)
Universal Dependencies 2.2 (CoNLL 2018)
See the download links at http://universaldependencies.org/.
For more information on the shared tasks, see
http://universaldependencies.org/conll17/
http://universaldependencies.org/conll18/
Contents:
conll17-ud-test-2017-05-09 ... CoNLL 2017 test data
conll18-ud-test-2018-05-06 ... CoNLL 2018 test data
conll18-ud-test-2018-05-06-for-conll17 ... CoNLL 2018 test data with metadata
and filenames modified so that it is digestible by the 2017 systems.
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.
The HMM-based Tagger is a software for morphological disambiguation (tagging) of Czech texts. The algorithm is statistical, based on the Hidden Markov Models.
General consensus in linguistics is that language context (or ''co-text'') plays crucial role in describing linguistic properties of language items. Isolated units are, as a corollary to this statement, inherently ambiguous (polysemous and/or polyfunctional). In this paper we describe the most influential forces leading to disambiguation of language units, specifically the role of n-gram length on its ambiguity.
The most influential achievement of corpus linguistics lies in the growing importance of context in the description of language. This is also reflected by context analysis which is introduced in this paper. Context analysis is an umbrella term for a bundle of methods sharing the same hypothesis: that all the features (form, meaning, function) of the language phenomena are mirrored by the context which they enter. It is important to emphasise that by the term ''context'', it is meant here not only one or two adjacent tokens in a particular text, but all the neighbouring units (e.g. words, lemmas, part of speech tags etc.) which co-occur with a given word in all of its instances in a corpus. The paper discusses various types of context (range, type of contextual units etc.) and their effect on the analysis. By comparing contexts of distinct words or word groups we may find out what the similarities and differences are between language units, phenomena or even groups of lexemes. This type of research was conducted here to determine the relations between parts of speech.
Lingua::Interset is a universal morphosyntactic feature set to which all tagsets of all corpora/languages can be mapped. Version 2.026 covers 37 different tagsets of 21 languages. Limited support of the older drivers for other languages (which are not included in this package but are available for download elsewhere) is also available; these will be fully ported to Interset 2 in future.
Interset is implemented as Perl libraries. It is also available via CPAN.
The MORČE tagger is a software for morphological disambiguation (part-of-speech tagging) of Czech text. The algorithm is statistical, based on an idea of so-called "Averaged Perceptron" published by Michael Collins in 2002.
Czech morphological dictionary developed originally by Jan Hajič as a spelling checker and lemmatization dictionary. Currently it contains full morphological information for each covered wordform, as well as some derivational, semantic and named entity information.
Czech morphological dictionary developed originally by Jan Hajič as a spelling checker and lemmatization dictionary. Currently it contains full morphological information for each covered wordform, as well as some derivational, semantic and named entity information.