Name | Czech – core | Czech – collections | other – core | other – collections | |
---|---|---|---|---|---|
Positions | Number of tokens | 105 239 198 | 117 981 673 | 233 509 950 | 1 560 655 498 |
Number of word forms | 84 718 325 | 89 645 545 | 194 055 340 | 1 229 043 791 | |
Structural attributes | Number of documents | 1 279 | 5 | 2 513 | 89 |
Number of div | 1 279 | 111 263 | 2 513 | 1 849 184 | |
Number of sentences | 7 250 794 | 13 588 082 | 14 377 637 | 143 478 514 | |
Further information | reference | YES | |||
representative | NO | ||||
publication date | 2015 | ||||
foreign languages | 38 | ||||
tagged languages | 20 | ||||
lemmatized languages | 17 |
After registration the corpus can be searched using a web interface. The registration is valid for all ICNC corpora with public access. If you already have a user name and password for the Czech part of the Czech National Corpus, you do not need to register for the parallel corpus.
InterCorp can be accessed via a standard web browser from the integrated search interface of the Czech National Corpus KonText. A tutorial is available in Czech and a brief summary also in English.
After signing a non-profit licence agreement, texts from InterCorp can also be acquired as bilingual files including shuffled pairs of sentences. Please contact us at the address below if you are interested.
New release of InterCorp is usually published once per year. With each new release, its size, possibly also the number of languages and the extent and quality of annotation may grow. Previous versions remain available (starting with release 6).
If you publish results based on InterCorp we would appreciate a link to the project site www.korpus.cz/intercorp. In your scientific publications please cite the following paper:
Čermák, F., Rosen, A. (2012). The case of InterCorp, a multilingual parallel corpus. International Journal of Corpus Linguistics. Vol. 13, no. 3, p. 411–427 (bibtex, electronic edition at ingentaConnect, preprint version).
For more references see the repository of bibliographical items based on the CNC. All references to work using InterCorp are welcome. See here for details.
When citing a specific part of InterCorp please use the reference displayed in KonText in the corpus description, e.g. as:
Rosen, A., Vavřín, M.: Korpus InterCorp – English, German1), version 7 from 19 Dec 2014. Institute of the Czech National Corpus, Charles University, Prague 2014. Available on-line: http://www.korpus.cz
The core of InterCorp consists mostly of fiction, manually aligned. Intercorp offers also a selection of fully automatically processed texts, so-called collections. The choice in the present release includes:
These texts have been aligned automatically: search results may include a higher number of misaligned segments. Morevore, the collections do not retain all texts from the original resource. This includes texts that have no Czech counterpart. Some texts from the Acquis Communautaire and Europarl corpora have been partially corrected or omitted – as a result, they may differ in form or size if compared with the original source. A similar selection was applied to the Open Subtitles database, where – as an additional reduction – only a single translation was selected per title and language. On the other hand, some metadata items missing in the original resource but detectable from context or other sources have been added.
Each text has a Czech counterpart. As a result, Czech is the pivot language: for every text there is a single Czech version (original or translation), aligned with one or more foreign-language versions. The total size of the available part of InterCorp in release 8 from May 2015 is 195 mil. words in the aligned foreign language texts in the core part and 1,229 mil. words in the collections (see Version history). The share of the core and the collections in the corpus can be seen in the following charts. The charts show the sizes in millions of words.
Language | Core | Syndicate | Presseurop | Acquis | Europarl | Subtitles | Total | |
---|---|---|---|---|---|---|---|---|
ar | Arabic | 34 | 0 | 0 | 0 | 0 | 0 | 34 |
be | Belarusian | 2 152 | 0 | 0 | 0 | 0 | 0 | 2 152 |
bg | Bulgarian | 5 240 | 0 | 0 | 13 816 | 9 083 | 0 | 28 140 |
ca | Catalan | 4 632 | 0 | 0 | 0 | 0 | 0 | 4 632 |
da | Danish | 3 016 | 0 | 0 | 21 679 | 13 915 | 14 429 | 53 042 |
de | German | 27 681 | 3 725 | 2 482 | 21 723 | 13 089 | 8 366 | 77 069 |
el | Greek | 0 | 0 | 0 | 25 069 | 15 403 | 23 714 | 64 187 |
en | English | 15 488 | 3 818 | 2 670 | 24 207 | 15 580 | 52 101 | 113 865 |
es | Spanish | 17 475 | 4 324 | 2 816 | 27 001 | 15 885 | 36 378 | 103 882 |
et | Estonian | 0 | 0 | 0 | 15 962 | 10 899 | 10 296 | 37 158 |
fi | Finnish | 3 426 | 0 | 0 | 16 455 | 10 175 | 15 097 | 45 154 |
fr | French | 9 170 | 4 393 | 2 928 | 27 351 | 17 178 | 25 961 | 86 983 |
he | Hebrew | 0 | 0 | 0 | 0 | 0 | 16 221 | 16 221 |
hi | Hindu | 408 | 0 | 0 | 0 | 0 | 0 | 408 |
hr | Croatian | 15 479 | 0 | 0 | 0 | 0 | 19 092 | 34 572 |
hu | Hungarian | 5 387 | 0 | 0 | 19 176 | 12 306 | 21 239 | 58 110 |
is | Icelandic | 0 | 0 | 0 | 0 | 0 | 1 584 | 1 584 |
it | Italian | 7 247 | 651 | 2 707 | 24 849 | 15 489 | 14 653 | 65 599 |
ja | Japanese | 0 | 0 | 0 | 0 | 0 | 113 | 113 |
lt | Lithuanian | 358 | 0 | 0 | 18 392 | 11 212 | 557 | 30 521 |
lv | Latvian | 1 336 | 0 | 0 | 18 744 | 11 688 | 280 | 32 050 |
mk | Macedonian | 3 741 | 0 | 0 | 0 | 0 | 1 877 | 5 619 |
ms | Malay | 0 | 0 | 0 | 0 | 0 | 3 520 | 3 520 |
mt | Maltese | 0 | 0 | 0 | 14 133 | 0 | 0 | 14 133 |
nl | Dutch | 9 961 | 313 | 2 955 | 24 746 | 15 563 | 29 362 | 82 903 |
no | Norwegian | 4 815 | 0 | 0 | 0 | 0 | 0 | 4 815 |
pl | Polish | 17 516 | 0 | 2 378 | 20 627 | 12 811 | 26 572 | 79 905 |
pt | Portuguese | 2 393 | 369 | 2 999 | 28 602 | 16 484 | 43 391 | 94 241 |
ro | Romanian | 3 432 | 0 | 2 737 | 8 199 | 9 446 | 34 128 | 57 944 |
ru | Russian | 3 337 | 3 174 | 0 | 0 | 0 | 6 885 | 13 397 |
sk | Slovak | 7 401 | 0 | 0 | 19 222 | 12 734 | 5 134 | 44 493 |
sl | Slovenian | 900 | 0 | 0 | 19 645 | 12 240 | 17 024 | 49 810 |
sq | Albanian | 0 | 0 | 0 | 0 | 0 | 2 003 | 2 003 |
sr | Serbian | 8 823 | 0 | 0 | 0 | 0 | 20 776 | 29 600 |
sv | Swedish | 8 138 | 0 | 0 | 20 585 | 13 840 | 14 693 | 57 258 |
tr | Turkish | 0 | 0 | 0 | 0 | 0 | 21 190 | 21 190 |
uk | Ukrainian | 5 054 | 0 | 0 | 0 | 0 | 246 | 5 300 |
vi | Vietnamese | 0 | 0 | 0 | 0 | 0 | 1 473 | 1 473 |
Subtotal | 194 055 | 20 769 | 24 676 | 430 195 | 265 029 | 488 372 | 1 423 098 | |
cs | Czech | 84 718 | 3 416 | 2 315 | 20 303 | 12 922 | 50 688 | 174 363 |
TOTAL | 278 773 | 24 185 | 26 991 | 450 498 | 277 951 | 539 060 | 1 597 462 |
N.B.: Each Czech text is counted only once, even though it may have more than one foreign counterpart.
Texts in the following languages have received some morphosyntactic annotation.
Language | Tags | Lemmas | Brief description | Detailed description | Tool |
---|---|---|---|---|---|
Bulgarian | ✔ | in English | TreeTagger | ||
Czech | ✔ | ✔ | in Czech in English2) | in English | Morče |
Dutch | ✔ | in Dutch | TreeTagger | ||
English | ✔ | ✔ | in English | in English + additions | TreeTagger |
Estonian | ✔ | ✔ | in Estonian and English | TreeTagger | |
Finnish | ✔ | ✔ | in English3) | OMorFi+HunPOS | |
French | ✔ | ✔ | in English | TreeTagger | |
German | ✔ | ✔ | in English4) | in German | RFTagger |
Hungarian | ✔ | in English | HunPos | ||
Icelandic | ✔ | ✔ | IceStagger | ||
Italian | ✔ | ✔ | in English | TreeTagger | |
Lithuanian | ✔ | ✔ | in Czech and English | in English | Author: Vidas Daudaravičius |
Norwegian | ✔ | ✔ | in English in Norwegian | analyzer, tagger | |
Polish | ✔ | ✔ | in English in Polish | in English | Morfeusz, TaKIPI |
Portuguese | ✔ | ✔ | Spanish | TreeTagger | |
Russian | ✔ | ✔ | in English | in English5) | TreeTagger |
Slovak | ✔ | ✔ | in Slovak | in Slovak | Radovan Garabík, Morče |
Slovene | ✔ | ✔ | English | totale | |
Spanish | ✔ | ✔ | in English | TreeTagger | |
Swedish | ✔ | ✔ | Stagger |
Queries including contracted forms into tagged or lemmatized texts may fail. This includes forms such as can't or I'm, which are split by the tagger into two parts (ca+n't and I+'m) with corresponding lemmas and tags. Similarly with Polish forms byłam or gdybyś (była+m and gdyby+ś). Tokenization may even introduce errors: gdzie ś za Wisłą. In this context, gdzieś is not a contraction. A query intended to find the whole contracted form should be typed in as a Phrase, with the split parts separated by a space. Only the individual parts of the contracted form are assigned a tag and a lemma.
Morphological tags including characters with a special meaning in regular expressions, e.g. “$” in the English tag “wp$”, must be preceded in queries by a backslash: tag=“wp\$”.
Structure | Attribute | Description | Values |
---|---|---|---|
doc | doc.id | unique document identifier | text |
doc.lang | language | ar / be / bg / ca / cs / da / de / el / en / es / et / fi / fr / he / hi / hr / hu / is / it / ja / lt / lv / mk / ms / mt / nb / nl / no / pl / pt / ro / ru / sk / sl / sq / sr / sv / sy / tr / uk / vi / zh | |
doc.version | version | number | |
doc.wordcount | document size in words | number | |
div | div.id | text identification | author's_last_name-shortened_title / _ACQUIS / _EUROPARL / _PRESSEUROP / _SUBTITLES / _SYNDICATE |
div.group | division in | Core / Acquis / Europarl / PressEurop / Subtitles / Syndicate | |
div.wordcount | number of words | number | |
div.author | author | last name, first name | |
div.title | full title | text | |
div.publisher | publisher | text | |
div.pubplace | publication place | text | |
div.pubyear | publication year | date | |
div.txtype | text type | discussions - transcripts / drama / fiction / journalism - commentaries / journalism - news / legal texts / nonfiction / other / poetry / subtitles | |
div.original | is the text an original? | Yes / No | |
div.srclang | language of the original | ar / as / az / be / bg / bl / bn / bo / bs / bt / ca / cr / cs / ct / cz / da / de / dk / eb / el / en / es / et / eu / fa / fi / fr / ga / gr / he / hi / hr / hu / hy / id / ie / is / it / ja / ka / ko / ku / lt / lv / mk / mn / ms / mt / my / ni / nl / no / pl / po / ps / pt / rm / ro / ru / se / sk / sl / sq / sr / sv / ta / th / ti / tl / tr / tu / uk / un / ur / vi / zh | |
div.translator | translator | last name, first name | |
div.transsex | translator's gender | F / M | |
div.authsex | author's gender | F / M | |
p | p.id | unique paragraph identifier | text |
s | s.id | unique sentence identifier | text |
Language of the original | |||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
↓ Language of the text | ar | be | bg | ca | cs | da | de | en | es | fi | fr | hi | hr | hu | it | lt | lv | mk | nl | no | pl | pt | ro | ru | sk | sl | sr | sv | uk | total | other |
ar | 1 | 1 | 1 | 3 | |||||||||||||||||||||||||||
be | 3 | 8 | 4 | 13 | 1 | 1 | 1 | 3 | 2 | 1 | 1 | 1 | 39 | ||||||||||||||||||
bg | 19 | 9 | 1 | 27 | 4 | 2 | 1 | 1 | 2 | 2 | 68 | ||||||||||||||||||||
ca | 1 | 16 | 3 | 12 | 5 | 1 | 2 | 3 | 1 | 1 | 45 | 1 | |||||||||||||||||||
cs | 1 | 3 | 19 | 1 | 267 | 9 | 134 | 242 | 127 | 24 | 95 | 2 | 26 | 1 | 20 | 1 | 7 | 1 | 30 | 7 | 49 | 21 | 39 | 56 | 3 | 8 | 58 | 6 | 1257 | ||
da | 6 | 9 | 12 | 27 | |||||||||||||||||||||||||||
de | 85 | 126 | 65 | 10 | 1 | 4 | 1 | 7 | 1 | 1 | 6 | 3 | 3 | 2 | 3 | 1 | 3 | 5 | 327 | ||||||||||||
en | 25 | 4 | 125 | 3 | 1 | 2 | 1 | 1 | 6 | 5 | 4 | 177 | 1 | ||||||||||||||||||
es | 1 | 25 | 8 | 29 | 126 | 1 | 6 | 7 | 1 | 4 | 2 | 3 | 213 | 1 | |||||||||||||||||
fi | 11 | 1 | 1 | 12 | 2 | 25 | 1 | 1 | 1 | 2 | 57 | 1 | |||||||||||||||||||
fr | 36 | 1 | 10 | 83 | 2 | 1 | 2 | 2 | 137 | ||||||||||||||||||||||
hi | 2 | 1 | 1 | 2 | 1 | 7 | |||||||||||||||||||||||||
hr | 1 | 71 | 15 | 52 | 11 | 2 | 4 | 26 | 6 | 7 | 1 | 3 | 4 | 1 | 1 | 8 | 213 | 2 | |||||||||||||
hu | 16 | 5 | 23 | 9 | 1 | 3 | 14 | 71 | |||||||||||||||||||||||
it | 4 | 4 | 21 | 9 | 1 | 3 | 19 | 3 | 1 | 3 | 68 | 1 | |||||||||||||||||||
lt | 8 | 2 | 2 | 1 | 1 | 2 | 1 | 17 | |||||||||||||||||||||||
lv | 22 | 2 | 1 | 1 | 7 | 2 | 1 | 36 | |||||||||||||||||||||||
mk | 15 | 1 | 16 | 1 | 1 | 1 | 2 | 1 | 3 | 2 | 2 | 4 | 49 | ||||||||||||||||||
nl | 24 | 3 | 33 | 7 | 3 | 3 | 30 | 2 | 2 | 3 | 3 | 6 | 119 | ||||||||||||||||||
no | 11 | 5 | 21 | 4 | 1 | 3 | 6 | 2 | 1 | 54 | |||||||||||||||||||||
pl | 36 | 8 | 97 | 10 | 2 | 8 | 2 | 1 | 1 | 3 | 1 | 46 | 4 | 6 | 1 | 5 | 231 | 1 | |||||||||||||
pt | 6 | 8 | 15 | 29 | |||||||||||||||||||||||||||
ro | 7 | 5 | 12 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 33 | 3 | |||||||||||||||||||
ru | 9 | 1 | 22 | 2 | 1 | 1 | 22 | 1 | 3 | 62 | 1 | ||||||||||||||||||||
sk | 55 | 2 | 5 | 1 | 1 | 2 | 56 | 122 | 18 | ||||||||||||||||||||||
sl | 7 | 1 | 2 | 1 | 2 | 2 | 15 | ||||||||||||||||||||||||
sr | 11 | 7 | 33 | 9 | 3 | 7 | 2 | 4 | 3 | 10 | 1 | 5 | 2 | 97 | 3 | ||||||||||||||||
sv | 11 | 4 | 23 | 7 | 2 | 1 | 1 | 50 | 99 | 1 | |||||||||||||||||||||
uk | 6 | 1 | 31 | 3 | 5 | 2 | 5 | 3 | 5 | 6 | 67 | ||||||||||||||||||||
total | 2 | 6 | 39 | 3 | 810 | 19 | 349 | 950 | 335 | 57 | 241 | 4 | 56 | 2 | 89 | 5 | 18 | 3 | 84 | 22 | 128 | 72 | 119 | 118 | 6 | 26 | 164 | 12 |
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