This machine translation test set contains 2223 Czech sentences collected within the FAUST project (https://ufal.mff.cuni.cz/grants/faust, http://hdl.handle.net/11234/1-3308).
Each original (noisy) sentence was normalized (clean1 and clean2) and translated to English independently by two translators.
The Feature-based (exponential model) Tagger is a fast implementation of the Czech tagger developed at UFAL and described in the PDT 1.0 documentation (Czech Language Tagging page). In order to get the best possible results, the tagger requires preprocessing by a Czech morphological module with a very high coverage. This module covers a superset of the Czech "FM" morphology. Both the morphological module and the tagger are supplied as binary executables, together with all necessary precompiled Czech data. Input must be in the ISO Latin 2 (iso-8859-2) code and follow the csts.dtd definition, and output is produced in the same way (ISO Latin 2 code, csts.dtd). (As is the case with many of the tools provided with PDT 1.0, both executables also accept - and then produce - a "simplified SGML", which is not a real, valid SGML, but simply contains at least the tags for words, punctuation, and sentence breaks, one item per line.)
This package contains data sets for development and testing of machine translation of medical search short queries between Czech, English, French, and German. The queries come from general public and medical experts. and This work was supported by the EU FP7 project Khresmoi (European Comission contract No. 257528). The language resources are distributed by the LINDAT/Clarin project of the Ministry of Education, Youth and Sports of the Czech Republic (project no. LM2010013).
We thank Health on the Net Foundation for granting the license for the English general public queries, TRIP database for granting the license for the English medical expert queries, and three anonymous translators and three medical experts for translating amd revising the data.
This package contains data sets for development and testing of machine translation of medical queries between Czech, English, French, German, Hungarian, Polish, Spanish ans Swedish. The queries come from general public and medical experts. This is version 2.0 extending the previous version by adding Hungarian, Polish, Spanish, and Swedish translations.
This package contains data sets for development and testing of machine translation of sentences from summaries of medical articles between Czech, English, French, and German. and This work was supported by the EU FP7 project Khresmoi (European Comission contract No. 257528). The language resources are distributed by the LINDAT/Clarin project of the Ministry of Education, Youth and Sports of the Czech Republic (project no. LM2010013). We thank all the data providers and copyright holders for providing the source data and anonymous experts for translating the sentences.
This package contains data sets for development (Section dev) and testing (Section test) of machine translation of sentences from summaries of medical articles between Czech, English, French, German, Hungarian, Polish, Spanish
and Swedish. Version 2.0 extends the previous version by adding Hungarian, Polish, Spanish, and Swedish translations.
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
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