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)
CzEng 1.0 is the fourth release of a sentence-parallel Czech-English corpus compiled at the Institute of Formal and Applied Linguistics (ÚFAL) freely available for non-commercial research purposes.
CzEng 1.0 contains 15 million parallel sentences (233 million English and 206 million Czech tokens) from seven different types of sources automatically annotated at surface and deep (a- and t-) layers of syntactic representation. and EuroMatrix Plus (FP7-ICT-2007-3-231720 of the EU and 7E09003+7E11051 of the Ministry of Education, Youth and Sports of the Czech Republic),
Faust (FP7-ICT-2009-4-247762 of the EU and 7E11041 of the Ministry of Education, Youth and Sports of the Czech Republic),
GAČR P406/10/P259,
GAUK 116310,
GAUK 4226/2011
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,
The PADT project might be summarized as an open-ended activity of the Center for Computational Linguistics, the Institute of Formal and Applied Linguistics, and the Institute of Comparative Linguistics, Charles University in Prague, resting in multi-level annotation of Arabic language resources in the light of the theory of Functional Generative Description (Sgall et al., 1986; Hajičová and Sgall, 2003).
Tamil Dependency Treebank version 0.1 (TamilTB.v0.1) is an attempt to develop a syntactically annotated corpora for Tamil. TamilTB.v0.1 contains 600 sentences enriched with manual annotation of morphology and dependency syntax in the style of Prague Dependency Treebank. TamilTB.v0.1 has been created at the Institute of Formal and Applied Linguistics, Charles University in Prague.
We release a sizeable monolingual Urdu corpus automatically tagged with part-of-speech tags. We extend the work of Jawaid and Bojar (2012) who use three different taggers and then apply a voting scheme to disambiguate among the different choices suggested by each tagger. We run this complex ensemble on a large monolingual corpus and release the both plain and tagged corpora. and it is supported by the MosesCore project sponsored by the European Commission’s Seventh Framework Programme (Grant Number 288487).