The PARSEME shared task aims at identifying verbal MWEs in running texts. Verbal MWEs include idioms (let the cat out of the bag), light verb constructions (make a decision), verb-particle constructions (give up), and inherently reflexive verbs (se suicider 'to suicide' in French). VMWEs were annotated according to the universal guidelines in 18 languages. The corpora are provided in the parsemetsv format, inspired by the CONLL-U format.
For most languages, paired files in the CONLL-U format - not necessarily using UD tagsets - containing parts of speech, lemmas, morphological features and/or syntactic dependencies are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe).
This item contains training and test data, tools and the universal guidelines file.
This paper deals with an automatic part-of-speech disambiguation of Czech texts containing the word to (E. it) in fixed collocations used especially in spoken Czech, and, moreover, with case identification of the pronominal reading of this word. The word to is ambiguous: the result of automatic morphological analysis of this word is either the pronominal lemma ten (it) as a nominative/accusative singular neuter, or the particle lemma to. It is very difficult to automatically distinguish the nonprepositional nominative and accusative case in Czech texts. Therefore, the paper primarily focuses on to as a particle. The software module performing automatic identification of collocations in Czech corpus texts is part of the automatic morphological rule-based disambiguation used for tagging texts of synchronic Czech in the corpora of the SYN series: it deals mainly with the disam-biguation of nongrammatical collocations and phrases. The paper focuses on fixed ex-pressions listed in the Dictionary of Czech Phraseology and Idiomatics and is based on the description of automatic identification and classification of collocations comprising the word to in the SYN2010 corpus. Also, examples (primarily idioms) are presented where automatic disambiguation using general grammatical rules yields unreliable results.
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.
Corpus of contemporary written (printed) Czech sized 3.6 GW (i.e. 4.3 billion tokens). It covers mostly the period of 1990–2014 and it is a traditional corpus (as opposed to the web-crawled corpora) with rich metadata containing bibliographical information etc. Although it contains a wide range of text types (fiction, non-fiction, newspapers), the newspapers prevail noticeably. The corpus is lemmatized and morphologically annotated by a combination of stochastic and rule-based methods.
The corpus is provided in a (semi-XML) vertical format used as an input to the Manatee query engine. The data thus correspond to the corpus available via the KonText query interface to registered users of the CNC at http://www.korpus.cz with one important exception: the corpus are shuffled, i.e. divided into blocks sized max. 100 words (respecting the sentence boundaries) with ordering randomized within the given document.
Corpus of contemporary written (printed) Czech sized 4.7 GW (i.e. 5.7 billion tokens). It covers mostly the 1990-2019 period and features rich metadata including detailed bibliographical information, text-type classification etc. SYN v9 contains a wide variety of text types (fiction, non-fiction, newspapers), but the newspapers prevail noticeably. The corpus is lemmatized and morphologically tagged by the new CNC tagset first utilized for the annotation of the SYN2020 corpus.
SYN v9 is provided in a CoNLL-U-like vertical format used as an input to the Manatee query engine. The data thus correspond to the corpus available via the KonText query interface to the registered users of CNC at http://www.korpus.cz with one important exception: the corpus is shuffled, i.e. divided into blocks sized max. 100 words (respecting the sentence boundaries) with ordering randomized within the given document.
Representative corpus of contemporary written Czech sized 100 MW. It was created as a representation of printed language from 2010–2014 containing a wide range of text types (fiction, professional literature, newspapers etc.). The corpus is lemmatized, morphologically and syntactically annotated by a combination of stochastic and rule-based methods. The corpus is provided in a (semi-XML) vertical format used as an input to the Manatee query engine. The data thus correspond to the corpus available via the KonText query interface to registered users of the CNC with one important exception: they are shuffled, i.e. divided into blocks sized max. 100 words (respecting the sentence boundaries) with ordering randomized within the given document.