ParaDi 2.0. is a dictionary of single verb paraphrases of Czech verbal multiword expressions - light verb constructions and idiomatic verb constructions. Moreover, it provides an elaborated set of morphological, syntactic and semantic features, including information on aspectual counterparts of verbs or paraphrasability conditions of given verbs.
The format of ParaDi has been designed with respect to both human and machine readability - the dictionary is represented as a plain table in TSV format, as it is a flexible and language-independent data format.
ParaDi 2.0. is a dictionary of single verb paraphrases of Czech verbal multiword expressions - light verb constructions and idiomatic verb constructions. Moreover, it provides an elaborated set of morphological, syntactic and semantic features, including information on aspectual counterparts of verbs or paraphrasability conditions of given verbs.
The format of ParaDi has been designed with respect to both human and machine readability - the dictionary is represented as a plain table in TSV format, as it is a flexible and language-independent data format.
Annotation of named entities to the existing source Parallel Global Voices, ces-eng language pair. The named entity annotations distinguish four classes: Person, Organization, Location, Misc. The annotation is in the IOB schema (annotation per token, beginning + inside of the multi-word annotation). NEL annotation contains Wikidata Qnames.
ParCorFull is a parallel corpus annotated with full coreference chains that has been created to address an important problem that machine translation and other multilingual natural language processing (NLP) technologies face -- translation of coreference across languages. Our corpus contains parallel texts for the language pair English-German, two major European languages. Despite being typologically very close, these languages still have systemic differences in the realisation of coreference, and thus pose problems for multilingual coreference resolution and machine translation. Our parallel corpus covers the genres of planned speech (public lectures) and newswire. It is richly annotated for coreference in both languages, including annotation of both nominal coreference and reference to antecedents expressed as clauses, sentences and verb phrases. This resource supports research in the areas of natural language processing, contrastive linguistics and translation studies on the mechanisms involved in coreference translation in order to develop a better understanding of the phenomenon.
The ParCzech 3.0 corpus is the third version of ParCzech consisting of stenographic protocols that record the Chamber of Deputies’ meetings held in the 7th term (2013-2017) and the current 8th term (2017-Mar 2021). The protocols are provided in their original HTML format, Parla-CLARIN TEI format, and the format suitable for Automatic Speech Recognition. The corpus is automatically enriched with the morphological, syntactic, and named-entity annotations using the procedures UDPipe 2 and NameTag 2. The audio files are aligned with the texts in the annotated TEI files.
The ParCzech 4.0 corpus consists of stenographic protocols that record the Chamber of Deputies' meetings in the 7th term (2013-2017), the 8th term (2017-2021) and the current 9th term (2021-Jul 2023). The protocols are provided in their original HTML format, Parla-CLARIN TEI format. The corpus is automatically enriched with the morphological, syntactic, and named-entity annotations using the procedures UDPipe 2 and NameTag 2. The audio files are aligned with the texts in the annotated TEI files.
The audio files in this corpus are available in AudioPSP 24.01 corpus (http://hdl.handle.net/11234/1-5404).
This corpus covers the same period as ParlaMint-CZ corpus v4.0 (http://hdl.handle.net/11356/1860). ParCzech corpus follows and extends the ParlaMint schema. Both annotated and non-annotated versions include hypertext references to voting and parliamentary prints. In addition to ParlaMint's recommendation, the annotated version contains source audio alignment, PDT xtag, and more detailed CNEC2.0 named entity categorization.
The ParCzech PS7 1.0 corpus is the very first member of the corpus family of data coming from the Parliament of the Czech Republic. ParCzech PS7 1.0 consists of stenographic protocols that record the Chamber of Deputies' meetings held in the 7th term between 2013-2017. The audio recordings are available as well. Transcripts are provided in the original HTML as harvested, and also converted into TEI-derived XML format for use in TEITOK corpus manager. The corpus is automatically enriched with the morphological and named-entity annotations using the procedures MorphoDita and NameTag.
The ParCzech PS7 2.0 corpus is the second version of ParCzech PS7 consisting of stenographic protocols that record the Chamber of Deputies' meetings held in the 7th term between 2013-2017. The protocols are provided in their original HTML format, TEI format and TEI-derived format to make them searchable in the TEITOK corpus manager. Their audio recordings are available as well. The corpus is automatically enriched with the morphological, syntactic, and named-entity annotations using the procedures UDPipe 2 and NameTag 2.
This multilingual resource contains corpora in which verbal MWEs have been manually annotated. VMWEs include idioms (let the cat out of the bag), light-verb constructions (make a decision), verb-particle constructions (give up), inherently reflexive verbs (help oneself), and multi-verb constructions (make do). This is the first release of the corpora without an associated shared task. Previous version (1.2) was associated with the PARSEME Shared Task on semi-supervised Identification of Verbal MWEs (2020). The data covers 26 languages corresponding to the combination of the corpora for all previous three editions (1.0, 1.1 and 1.2) of the corpora. VMWEs were annotated according to the universal guidelines. The corpora are provided in the cupt format, inspired by the CONLL-U format. Morphological and syntactic information, including 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). All corpora are split into training, development and test data, following the splitting strategy adopted for the PARSEME Shared Task 1.2. The annotation guidelines are available online: https://parsemefr.lis-lab.fr/parseme-st-guidelines/1.3 The .cupt format is detailed here: https://multiword.sourceforge.net/cupt-format/