Lexical network AdjDeriNet consists of pairs of base adjectives and their derivatives. It contains nearly 18 thousand base adjectives that are base words for more than 26 thousand lexemes of several parts of speech.
The dataset contains 4731 frozen continuous Czech multiword expressions. Inflectional word forms are generated for those MWEs where applicable. In total, the dataset contains 24,807 MWE forms.
Czech subjectivity lexicon, i.e. a list of subjectivity clues for sentiment analysis in Czech. The list contains 4626 evaluative items (1672 positive and 2954 negative) together with their part of speech tags, polarity orientation and source information.
The core of the Czech subjectivity lexicon has been gained by automatic translation of a freely available English subjectivity lexicon downloaded from http://www.cs.pitt.edu/mpqa/subj_lexicon.html. For translating the data into Czech, we used parallel corpus CzEng 1.0 containing 15 million parallel sentences (233 million English and 206 million Czech tokens) from seven different types of sources automatically annotated at surface and deep layers of syntactic representation. Afterwards, the lexicon has been manually refined by an experienced annotator. and The work on this project has been supported by the GAUK 3537/2011 grant and by SVV project number 267 314.
The EBUContentGenre is a thesaurus containing the hierarchical description of various genres utilized in the TV broadcasting industry. This thesaurus is a part of a complex metadata specification called EBUCore intended for multifaceted description of audiovisual content. EBUCore (http://tech.ebu.ch/docs/tech/tech3293v1_3.pdf) is a set of descriptive and technical metadata based on the Dublin Core and adapted to media. EBUCore is the flagship metadata specification of European Broadcasting Union, the largest professional association of broadcasters around the world. It is developed and maintained by EBU's Technical Department (http://tech.ebu.ch). The translated thesaurus can be used for effective cataloguing of (mostly TV) audiovisual content and consequent development of systems for automatic cataloguing (topic/genre detection). and Technology Agency of the Czech Republic, project No. TA01011264
CzeDLex 0.5 is a pilot version of a lexicon of Czech discourse connectives. The lexicon contains connectives partially automatically extracted from the Prague Discourse Treebank 2.0 (PDiT 2.0), a large corpus annotated manually with discourse relations. The most frequent entries in the lexicon (covering more than 2/3 of the discourse relations annotated in the PDiT 2.0) have been manually checked, translated to English and supplemented with additional linguistic information.
CzeDLex 0.6 is the second development version of the lexicon of Czech discourse connectives. The lexicon contains connectives partially automatically extracted from the Prague Discourse Treebank 2.0 (PDiT 2.0), a large corpus annotated manually with discourse relations. The most frequent entries in the lexicon (76 out of total 204 entries, covering more than 90% of the discourse relations annotated in PDiT 2.0), have been manually checked, translated to English and supplemented with additional linguistic information.
CzeDLex 0.7 is the third development version of the Lexicon of Czech discourse connectives. The lexicon contains connectives partially automatically extracted from the Prague Discourse Treebank 2.0 (PDiT 2.0) and, as a supplementary resource, the Czech part of the Prague Czech–English Dependency Treebank with discourse annotation projected from the Penn Discourse Treebank 3.0. The most frequent entries in the lexicon (131 out of total 218 entries, covering more than 95% of discourse relations annotated in PDiT 2.0), have been manually checked, translated to English and supplemented with additional linguistic information.
CzeDLex 1.0 is the first production version (the fourth development version) of the Lexicon of Czech discourse connectives. The lexicon contains connectives partially automatically extracted from resources annotated manually with discourse relations: the Prague Discourse Treebank 2.0 (PDiT 2.0) as the primary resource, and two supplementary resources: (i) the Czech part of the Prague Czech–English Dependency Treebank with discourse annotation projected from the Penn Discourse Treebank 3.0, and (ii) a thousand sentences selected from various fiction novels and transcriptions of public speeches. All 200 entries in the lexicon have been manually checked, translated to English and supplemented with additional linguistic information.
The CzEngClass synonym verb lexicon is a result of a project investigating semantic ‘equivalence’ of verb senses and their valency behavior in parallel Czech-English language resources, i.e., relating verb meanings with respect to contextually-based verb synonymy. The lexicon entries are linked to PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F), EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2), CzEngVallex (http://hdl.handle.net/11234/1-1512), FrameNet (https://framenet.icsi.berkeley.edu/fndrupal/), VerbNet (http://verbs.colorado.edu/verbnet/index.html), PropBank (http://verbs.colorado.edu/%7Empalmer/projects/ace.html), Ontonotes (http://verbs.colorado.edu/html_groupings/), and Czech (http://hdl.handle.net/11858/00-097C-0000-0001-4880-3) and English Wordnets (https://wordnet.princeton.edu/). Part of the dataset is a file reflecting annotators choices for assignment of verbs to classes.
The CzEngClass synonym verb lexicon is a result of a project investigating semantic ‘equivalence’ of verb senses and their valency behavior in parallel Czech-English language resources, i.e., relating verb meanings with respect to contextually-based verb synonymy. The lexicon entries are linked to PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F), EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2), CzEngVallex (http://hdl.handle.net/11234/1-1512), FrameNet (https://framenet.icsi.berkeley.edu/fndrupal/), VerbNet (http://verbs.colorado.edu/verbnet/index.html), PropBank (http://verbs.colorado.edu/%7Empalmer/projects/ace.html), Ontonotes (http://verbs.colorado.edu/html_groupings/), and Czech (http://hdl.handle.net/11858/00-097C-0000-0001-4880-3) and English Wordnets (https://wordnet.princeton.edu/). Part of the dataset are files reflecting annotators choices and agreement for assignment of verbs to classes.