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)
A slightly modified version of the Czech Wordnet. This is the version used to annotate "The Lexico-Semantic Annotation of PDT using Czech WordNet": http://hdl.handle.net/11858/00-097C-0000-0001-487A-4
The Czech WordNet was developed by the Centre of Natural Language Processing at the Faculty of Informatics, Masaryk University, Czech Republic.
The Czech WordNet captures nouns, verbs, adjectives, and partly adverbs, and contains 23,094 word senses (synsets). 203 of these were created or modified by UFAL during correction of annotations. This version of WordNet was used to annotate word senses in PDT: http://hdl.handle.net/11858/00-097C-0000-0001-487A-4
A more recent version of Czech WordNet is distributed by ELRA: http://catalog.elra.info/product_info.php?products_id=1089 and 1ET201120505, LM2010013
Annotation of extended textual coreference and bridging relations in the Prague Dependency Treebank 2.0 and project LINDAT-Clarin LM2010013, grant GAČR GA405/09/0729
Syntactic (including deep-syntactic - tectogrammatical) annotation of user-generated noisy sentences. The annotation was made on Czech-English and English-Czech Faust Dev/Test sets.
The English data includes manual annotations of English reference translations of Czech source texts. This texts were translated independently by two translators. After some necessary cleanings, 1000 segments were randomly selected for manual annotation. Both the reference translations were annotated, which means 2000 annotated segments in total.
The Czech data includes manual annotations of Czech reference translations of English source texts. This texts were translated independently by three translators. After some necessary cleanings, 1000 segments were randomly selected for manual annotation. All three reference translations were annotated, which means 3000 annotated segments in total.
Faust is part of PDT-C 1.0 (http://hdl.handle.net/11234/1-3185).
HindEnCorp parallel texts (sentence-aligned) come from the following sources:
Tides, which contains 50K sentence pairs taken mainly from news articles. This dataset was originally col- lected for the DARPA-TIDES surprise-language con- test in 2002, later refined at IIIT Hyderabad and provided for the NLP Tools Contest at ICON 2008 (Venkatapathy, 2008).
Commentaries by Daniel Pipes contain 322 articles in English written by a journalist Daniel Pipes and translated into Hindi.
EMILLE. This corpus (Baker et al., 2002) consists of three components: monolingual, parallel and annotated corpora. There are fourteen monolingual sub- corpora, including both written and (for some lan- guages) spoken data for fourteen South Asian lan- guages. The EMILLE monolingual corpora contain in total 92,799,000 words (including 2,627,000 words of transcribed spoken data for Bengali, Gujarati, Hindi, Punjabi and Urdu). The parallel corpus consists of 200,000 words of text in English and its accompanying translations into Hindi and other languages.
Smaller datasets as collected by Bojar et al. (2010) include the corpus used at ACL 2005 (a subcorpus of EMILLE), a corpus of named entities from Wikipedia (crawled in 2009), and Agriculture domain parallel corpus.

For the current release, we are extending the parallel corpus using these sources:
Intercorp (Čermák and Rosen,2012) is a large multilingual parallel corpus of 32 languages including Hindi. The central language used for alignment is Czech. Intercorp’s core texts amount to 202 million words. These core texts are most suitable for us because their sentence alignment is manually checked and therefore very reliable. They cover predominately short sto- ries and novels. There are seven Hindi texts in Inter- corp. Unfortunately, only for three of them the English translation is available; the other four are aligned only with Czech texts. The Hindi subcorpus of Intercorp contains 118,000 words in Hindi.
TED talks 3 held in various languages, primarily English, are equipped with transcripts and these are translated into 102 languages. There are 179 talks for which Hindi translation is available.
The Indic multi-parallel corpus (Birch et al., 2011; Post et al., 2012) is a corpus of texts from Wikipedia translated from the respective Indian language into English by non-expert translators hired over Mechanical Turk. The quality is thus somewhat mixed in many respects starting from typesetting and punctuation over capi- talization, spelling, word choice to sentence structure. A little bit of control could be in principle obtained from the fact that every input sentence was translated 4 times. We used the 2012 release of the corpus.
Launchpad.net is a software collaboration platform that hosts many open-source projects and facilitates also collaborative localization of the tools. We downloaded all revisions of all the hosted projects and extracted the localization (.po) files.
Other smaller datasets. This time, we added Wikipedia entities as crawled in 2013 (including any morphological variants of the named entitity that appears on the Hindi variant of the Wikipedia page) and words, word examples and quotes from the Shabdkosh online dictionary. and LM2010013,
Hindi monolingual corpus. It is based primarily on web crawls performed using various tools and at various times. Since the web is a living data source, we treat these crawls as completely separate sources, despite they may overlap. To estimate the magnitude of this overlap, we compared the total number of segments if we concatenate the individual sources (each source being deduplicated on its own) with the number of segments if we de-duplicate all sources to- gether. The difference is just around 1%, confirming, that various web crawls (or their subsequent processings) differ significantly.
HindMonoCorp contains data from:
Hindi web texts, a monolingual corpus containing mainly Hindi news articles has already been collected and released by Bojar et al. (2008). We use the HTML files as crawled for this corpus in 2010 and we add a small crawl performed in 2013 and re-process them with the current pipeline. These sources are denoted HWT 2010 and HWT 2013 in the following.
Hindi corpora in W2C have been collected by Martin Majliš during his project to automatically collect corpora in many languages (Majliš and Žabokrtský, 2012). There are in fact two corpora of Hindi available—one from web harvest (W2C Web) and one from the Wikipedia (W2C Wiki).
SpiderLing is a web crawl carried out during November and December 2013 using SpiderLing (Suchomel and Pomikálek, 2012). The pipeline includes extraction of plain texts and deduplication at the level of documents, see below.
CommonCrawl is a non-profit organization that regu- larly crawls the web and provides anyone with the data. We are grateful to Christian Buck for extracting plain text Hindi segments from the 2012 and 2013-fall crawls for us.
Intercorp – 7 books with their translations scanned and manually alligned per paragraph
RSS Feeds from Webdunia.com and the Hindi version of BBC International followed by our custom crawler from September 2013 till January 2014. and LM2010013,
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 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.
Texts
The Prague Czech-English Dependency Treebank 2.0 (PCEDT 2.0) is a major update of the Prague Czech-English Dependency Treebank 1.0 (LDC2004T25). It is a manually parsed Czech-English parallel corpus sized over 1.2 million running words in almost 50,000 sentences for each part.
Data
The English part contains the entire Penn Treebank - Wall Street Journal Section (LDC99T42). The Czech part consists of Czech translations of all of the Penn Treebank-WSJ texts. The corpus is 1:1 sentence-aligned. An additional automatic alignment on the node level (different for each annotation layer) is part of this release, too. The original Penn Treebank-like file structure (25 sections, each containing up to one hundred files) has been preserved. Only those PTB documents which have both POS and structural annotation (total of 2312 documents) have been translated to Czech and made part of this release.
Each language part is enhanced with a comprehensive manual linguistic annotation in the PDT 2.0 style (LDC2006T01, Prague Dependency Treebank 2.0). The main features of this annotation style are:
dependency structure of the content words and coordinating and similar structures (function words are attached as their attribute values)
semantic labeling of content words and types of coordinating structures
argument structure, including an argument structure ("valency") lexicon for both languages
ellipsis and anaphora resolution.
This annotation style is called tectogrammatical annotation and it constitutes the tectogrammatical layer in the corpus. For more details see below and documentation.
Annotation of the Czech part
Sentences of the Czech translation were automatically morphologically annotated and parsed into surface-syntax dependency trees in the PDT 2.0 annotation style. This annotation style is sometimes called analytical annotation; it constitutes the analytical layer of the corpus. The manual tectogrammatical (deep-syntax) annotation was built as a separate layer above the automatic analytical (surface-syntax) parse. A sample of 2,000 sentences was manually annotated on the analytical layer.
Annotation of the English part
The resulting manual tectogrammatical annotation was built above an automatic transformation of the original phrase-structure annotation of the Penn Treebank into surface dependency (analytical) representations, using the following additional linguistic information from other sources:
PropBank (LDC2004T14)
VerbNet
NomBank (LDC2008T23)
flat noun phrase structures (by courtesy of D. Vadas and J.R. Curran)
For each sentence, the original Penn Treebank phrase structure trees are preserved in this corpus together with their links to the analytical and tectogrammatical annotation. and Ministry of Education of the Czech Republic projects No.:
MSM0021620838
LC536
ME09008
LM2010013
7E09003+7E11051
7E11041
Czech Science Foundation, grants No.:
GAP406/10/0875
GPP406/10/P193
GA405/09/0729
Research funds of the Faculty of Mathematics and Physics, Charles University, Czech Republic, Grant Agency of the Academy of Sciences of the Czech Republic: No. 1ET101120503
Students participating in this project have been running their own student grants from the Grant Agency of the Charles University, which were connected to this project. Only ongoing projects are mentioned: 116310, 158010, 3537/2011
Also, this work was funded in part by the following projects sponsored by the European Commission:
Companions, No. 034434
EuroMatrix, No. 034291
EuroMatrixPlus, No. 231720
Faust, No. 247762
Ministerstvo školství, mládeže a tělovýchovy České republiky@@LM2010013@@LINDAT/CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat@@nationalFunds@@✖[remove]15