Lexical Annotation Workbench (LAW) is an integrated environment for morphological annotation. It supports simple morphological annotation (assigning a lemma and tag to a word), integration and comparison of different annotations of the same text, searching for particular word, tag etc.
This dataset contains annotation of PDT using Czech WordNet ontology: http://hdl.handle.net/11858/00-097C-0000-0001-4880-3
Data is stored in PML format. This is a stand-off annotation and for most use cases it requires PDT 2.0 and the Czech WordNet 1.9 PDT that we have used for annotation. and 1ET100300517, 1ET201120505
GeCzLex 1.0 is an online electronic resource for translation equivalents of Czech and German discourse connectives. It contains anaphoric connectives for both languages and their possible translations documented in bilingual parallel corpora (not necessarily anaphoric). The entries have been interlinked via semantic annotation of the connectives (taken from monolingual lexicons of connectives CzeDLex and DiMLex) according to the PDTB 3 sense taxonomy and translation possibilities aquired from the Czech and German parallel data of the Intercorp project. The lexicon is the first bilingual inventory of connectives with linkage on the level of individual pairs (connective + discourse sense).
LiFR-Law is a corpus of Czech legal and administrative texts with measured reading comprehension and a subjective expert annotation of diverse textual properties based on the Hamburg Comprehensibility Concept (Langer, Schulz von Thun, Tausch, 1974). It has been built as a pilot data set to explore the Linguistic Factors of Readability (hence the LiFR acronym) in Czech administrative and legal texts, modeling their correlation with actually observed reading comprehension. The corpus is comprised of 18 documents in total; that is, six different texts from the legal/administration domain, each in three versions: the original and two paraphrases. Each such document triple shares one reading-comprehension test administered to at least thirty readers of random gender, educational background, and age. The data set also captures basic demographic information about each reader, their familiarity with the topic, and their subjective assessment of the stylistic properties of the given document, roughly corresponding to the key text properties identified by the Hamburg Comprehensibility Concept.
LiFR-Law is a corpus of Czech legal and administrative texts with measured reading comprehension and a subjective expert annotation of diverse textual properties based on the Hamburg Comprehensibility Concept (Langer, Schulz von Thun, Tausch, 1974). It has been built as a pilot data set to explore the Linguistic Factors of Readability (hence the LiFR acronym) in Czech administrative and legal texts, modeling their correlation with actually observed reading comprehension. The corpus is comprised of 18 documents in total; that is, six different texts from the legal/administration domain, each in three versions: the original and two paraphrases. Each such document triple shares one reading-comprehension test administered to at least thirty readers of random gender, educational background, and age. The data set also captures basic demographic information about each reader, their familiarity with the topic, and their subjective assessment of the stylistic properties of the given document, roughly corresponding to the key text properties identified by the Hamburg Comprehensibility Concept.
Changes to the previous version and helpful comments
• File names of the comprehension test results (self-explanatory)
• Corrected one erroneous automatic evaluation rule in the multiple-choice evaluation (zahradnici_3,
TRUE and FALSE had been swapped)
• Evaluation protocols for both question types added into Folder lifr_formr_study_design
• Data has been cleaned: empty responses to multiple-choice questions were re-inserted. Now, all surveys
are considered complete that have reader’s subjective text evaluation complete (these were placed at
the very end of each survey).
• Only complete surveys (all 7 content questions answered) are represented. We dropped the replies of
six users who did not complete their surveys.
• A few missing responses to open questions have been detected and re-inserted.
• The demographic data contain all respondents who filled in the informed consent and the demographic
details, with respondents who did not complete any test survey (but provided their demographic
details) in a separate file. All other data have been cleaned to contain only responses by the regular
respondents (at least one completed survey).
Corpus of Czech educational texts for readability studies, with paraphrases, measured reading comprehension, and a multi-annotator subjective rating of selected text features based on the Hamburg Comprehensibility Concept
Corpus of Czech educational texts for readability studies, with paraphrases, measured reading comprehension, and a multi-annotator subjective rating of selected text features based on the Hamburg Comprehensibility Concept
Source code of the LINDAT Translation service frontend. The service provides a UI and a simple rest api that accesses machine translation models served by tensorflow serving.
The most recent version of the code is available at https://github.com/ufal/lindat_translation.
One of the goals of LINDAT/CLARIN Centre for Language Research Infrastructure is to provide technical background to institutions or researchers who wants to share their tools and data used for research in linguistics or related research fields. The digital repository is built on a highly customised DSpace platform. and LM2010013 - FULLY SUPPORTED BY THE MINISTRY OF EDUCATION, SPORTS AND YOUTH OF THE CZECH REPUBLIC
One of the goals of LINDAT/CLARIN Centre for Language Research Infrastructure is to provide technical background to institutions or researchers who wants to share their tools and data used for research in linguistics or related research fields. The digital repository is built on a highly customised DSpace platform. and LM2010013 - FULLY SUPPORTED BY THE MINISTRY OF EDUCATION, SPORTS AND YOUTH OF THE CZECH REPUBLIC