Additional three Czech reference translations of the whole WMT 2011 data set (http://www.statmt.org/wmt11/test.tgz), translated from the German originals. Original segmentation of the WMT 2011 data is preserved. and This project has been sponsored by the grants GAČR P406/11/1499 and EuroMatrixPlus (FP7-ICT-2007-3-231720 of the EU and 7E09003+7E11051 of the Ministry of Education, Youth and Sports of the Czech Republic)
This dataset contains a number of user product reviews which are publicly available on the website of an established Czech online shop with electronic devices. Each review consists of negative and positive aspects of the product. This setting pushes the customer to rate important characteristics.
We have selected 2000 positive and negative segments from these reviews and manually tagged their targets. Additionally, we selected 200 of the longest reviews and annotated them in the same way. The targets were either aspects of the evaluated product or some general attributes (e.g. price, ease of use).
Automatically generated spelling correction corpus for Czech (Czesl-SEC-AG) is a corpus containg text with automatically generated spelling errors. To create spelling errors, a character error model containing probabilities of character substitution, insertion, deletion and probabilities of swaping two adjacent characters is used. Besides these probabilities, also the probabilities of changing character casing are considered. The original clean text on which the spelling errors were generated is PDT3.0 (http://hdl.handle.net/11858/00-097C-0000-0023-1AAF-3). The original train/dev/test sentence split of PDT3.0 corpus is preserved in this dataset.
Besides the data with artificial spelling errors, we also publish texts from which the character error model was created. These are the original manual transcript of an audiobook Švejk and its corrected version performed by authors of Korektor (http://ufal.mff.cuni.cz/korektor). These data are similarly to CzeSL Grammatical Error Correction Dataset (CzeSL-GEC: http://hdl.handle.net/11234/1-2143) processed into four sets based on error difficulty present.
Czech data - both train and test+eval sets, as well as the valency dictionary - for the CoNLL 2009 Shared Task. Documentation is included. The data are generated from PDT 2.0. LDC catalog number: LDC2009E34B and MSM 0021620838 (http://ufal.mff.cuni.cz:8080/bib/?section=grant&id=116488695895567&mode=view)
Czech trial (example) data for CoNLL 2009 Shared Task. The data are generated from PDT 2.0. LDC2009E32B and MSM 0021620838 (http://ufal.mff.cuni.cz:8080/bib/?section=grant&id=116488695895567&mode=view)
This is a Czech Named Entity Corpus 1.0 transformed into the CoNLL format. The original corpus can be downloaded from: http://hdl.handle.net/11858/00-097C-0000-0023-1B04-C. The CoNLL transformation is described in this publication: https://link.springer.com/chapter/10.1007/978-3-642-40585-3_20.
This is a Czech Named Entity Corpus 2.0 transformed into the CoNLL format. The original corpus can be downloaded from: http://hdl.handle.net/11858/00-097C-0000-0023-1B22-8. The CoNLL transformation is described in this publication: https://link.springer.com/chapter/10.1007/978-3-642-40585-3_20.
The presented Czech Named Entity Corpus 1.0 is the first publicly available corpus providing a large body of manually annotated named entities in Czech sentences, including a fine-grained classification. and 1ET101120503 (Integrace jazykových zdrojů za účelem extrakce informací z přirozených textů)
Czech Named Entity Corpus 1.1 fixes some issues of the Czech Named Entity Corpus 1.0: misannotated entities are fixed, all formats contain the same data, tmt format is replaced with treex format, all formats contain splitting into training, development and testing portion of the data. and SVV 267 314 (Teoretické základy informatiky a výpočetní lingvistiky), LM2010013 (LINDAT-CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat), GPP406/12/P175 (Vybrané derivační vztahy pro automatické zpracování češtiny), PRVOUK (PRVOUK)
Czech Named Entity Corpus 2.0 is a corpus of 8993 Czech sentences with manually annotated 35220 Czech named entities, classified according to a two-level hierarchy of 46 named entities. and SVV 267 314 (Teoretické základy informatiky a výpočetní lingvistiky), LM2010013 (LINDAT-CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat), GPP406/12/P175 (Vybrané derivační vztahy pro automatické zpracování češtiny), PRVOUK (PRVOUK)