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InterCorp Release 13

Name Czech – core Czech – collections other – core other – collections
Positions Number of tokens 141,032,521 116,673,043 394,042,551 1,550,071,364
Number of word forms 113,838,505 89,819,773 327,968,369 1,223,270,610
Structural attributes Number of documents 1,657 30 3,993 282
Number of texts 1,657 111,951 3,993 1,843,528
Number of sentences 9,782,001 13,606,183 24,305,621 143,195,566
Further information reference YES
representative NO
publication date 2020
foreign languages 40
tagged languages 27
lemmatized languages 25

Access to the texts

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 KonText, the integrated search interface of the Czech National Corpus. A tutorial is available in Czech, for one of the ICNC corpora also in English and for InterCorp a 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 Martin Vavřín 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).

References

If you publish results based on InterCorp we would appreciate a link to the project site www.intercorp.korpus.cz. 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 based on 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., Zasina, A. J. (2020). The InterCorp Corpus – Czech1), version 13 of 1 November 2020. Institute of the Czech National Corpus, Charles University, Prague 2020. Available on-line: https://kontext.korpus.cz/

Texts in the corpus

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 13 published in November 2020 is 328 mil. words in the aligned foreign language texts in the core part and 1,223 mil. words in the collections. The number of words in the Czech texts is 114 mil. in the core part and 90 mil. 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 volumes in millions of words.

Setup of the parallel corpus – the core and collections


Setup of the parallel corpus – the core


Setup of the parallel corpus – collections

Corpus size in thousands of words

Language Core Syndicate Presseurop Acquis Europarl Subtitles Bible Total
ar Arabic 34 0 0 0 0 0 0 34
be Belarusian 5,718 0 0 0 0 0 0 5,718
bg Bulgarian 7,068 0 0 13,577 9,083 0 0 29,728
ca Catalan 7,938 0 0 0 0 0 736 8,674
da Danish 7,136 0 0 20,313 13,916 14,429 657 56,451
de German 37,633 4,704 2,483 20,610 13,088 8,392 724 87,634
el Greek 0 0 0 23,853 15,404 23,709 0 62,966
en English 33,569 4,856 2,670 22,902 15,576 52,106 730 132,409
es Spanish 26,554 5,614 2,859 26,262 16,249 36,650 0 114,187
et Estonian 0 0 0 14,896 10,899 10,298 0 36,093
fi Finnish 5,656 0 0 15,269 10,108 15,047 543 46,622
fr French 19,773 5,600 3,046 26,200 17,179 25,986 764 98,547
he Hebrew 0 0 0 0 0 16,221 0 16,221
hi Hindi 409 0 0 0 0 0 0 409
hr Croatian 21,923 0 0 0 0 19,048 571 41,543
hu Hungarian 6,444 0 0 17,852 12,198 21,115 0 57,609
is Icelandic 0 0 0 0 0 1,581 0 1,581
it Italian 14,525 1,252 2,747 23,771 15,494 14,700 684 73,174
ja Japanese 2,189 0 0 0 0 477 0 2,666
lt Lithuanian 421 0 0 17,316 11,213 558 471 29,979
lv Latvian 2,646 0 0 17,522 11,682 280 537 32,667
mk Macedonian 8,881 0 0 0 0 1,877 0 10,758
ms Malay 0 0 0 0 0 3,521 0 3,521
mt Maltese 0 0 0 13,935 0 0 0 13,935
nl Dutch 16,216 813 2,953 23,416 15,558 29,373 717 89,045
no Norwegian 7,727 0 0 0 0 0 722 8,449
pl Polish 26,200 0 2,380 19,604 12,817 26,576 583 88,161
pt Portuguese 4,981 554 2,782 24,598 15,193 41,468 706 90,282
rn Romani 14 0 0 0 0 0 0 14
ro Romanian 4,219 0 2,738 8,092 9,446 34,128 0 58,622
ru Russian 8,642 3,984 0 0 0 6,887 565 20,078
sk Slovak 8,543 0 0 18,399 12,727 5,133 561 45,363
sl Slovene 3,871 0 0 18,528 12,251 17,061 0 51,711
sq Albanian 0 0 0 0 0 2,003 0 2,003
sr Serbian 11,582 0 0 0 0 20,727 0 32,308
sv Swedish 15,790 0 0 19,542 13,784 14,666 638 64,419
tr Turkish 0 0 0 0 0 21,190 0 21,190
uk Ukrainian 11,459 0 0 0 0 244 596 12,299
vi Vietnamese 0 0 0 0 0 1,474 0 1,474
zh Chinese 127 240 0 0 0 2,247 0 2,614
Subtotal 327,887 27,616 24,658 406,459 263,864 489,169 11,504 1,551,157
cs Czech 113,839 4,351 2,310 19,085 12,908 50,604 562 203,658
TOTAL 441,725 31,967 26,968 425,543 276,772 539,774 12,066 1,754,815

N.B.: Each Czech text is counted only once, even though it may have more than one foreign counterpart.

Morphosyntactic annotation

Texts in the following languages have received some morphosyntactic annotation. The format and often even the meaning of categories encoded in the morphosyntactic tags differs in most languages. Thus for each tagged language we provide a link to the tagset description. After selecting CQL as the query type, the tagset description is available also from the KonText search interface.

Language Tags Lemmas Brief description Detailed description Tool
Belarusian in English****) in English****) UDPipe
Bulgarian in English in English TreeTagger
Catalan in English TreeTagger
Chinese in English in English ZPar v0.7.5
Croatian in English in English ReLDI Tagger
Czech in Czech and English in English Morče
Dutch in English TreeTagger
English in English in English + additions TreeTagger
Estonian in Estonian and English TreeTagger
Finnish in English*) in English*) OMorFi +HunPOS
French in English TreeTagger
German in English **) in German RFTagger
Hungarian in English RFTagger
Icelandic in English in English IceStagger
Italian in English TreeTagger
Japanese in English MeCab + Unidic
Latvian in Latvian LVTagger
Norwegian in English and Norwegian Oslo-Bergen Tagger
Polish in English and Polish in English Morfeusz, KRNNT
Portuguese in Spanish TreeTagger
Russian in English in English ***) TreeTagger
Slovak in Slovak and English in Slovak Radovan Garabík, Morče
Slovene in English ReLDI Tagger
Serbian in English in English ReLDI Tagger
Spanish in English TreeTagger
Swedish in Swedish and English Stagger
Ukrainian in English****) UDPipe

*) The corpus includes tags in a condensed form, e.g. V:Sg:Nom:Act:PrfPrc:Pos corresponds to [POS=V] [NUM=SG] [CASE=NOM] [VOICE=ACT] [PCP=PRFPRC] [CMP=POS]. Similarly, Pron:Pers:Sg:Ade:Up corresponds to [POS=PRON] [SUBCAT:PERS] [NUM:SG] [CASE=ADE] [CASECHANGE=UP].

**) Within a single morphological tag a colon rather than period is used as a separator of the individual categories, e.g. ADJA:Pos:Nom:Sg:Fem.

***) Tags in the corpus do not always correspond to those listed in the detailed description. Some morphological categories are omitted in the corpus tags, e.g. pronouns are always tagged only as “P-”. All tags, as used in ther corpus, are listed in the brief description.

****) The tag is in the UD (Universal Dependencies) format, components of the tag are separated by a vertical bar (|), e.g. the form школы in genitive singular is tagged as: NOUN|Animacy=Inan|Case=Gen|Gender=Fem|Number=Sing. The query can be specified in the same way as for other languages, treating the tag as a string, i.e.\ [tag="NOUN.*Case=Gen\|Gender=Fem.*"] or the tag components can be specified separately: [tag="Case=Gen" & tag="NOUN" & tag="Gender=Fem"] (the order of categories is not significant). The result is identical in either case.

Tag formats specified in tagset descriptions differ from those actually used in the corpus also in some other languages. Please check the tag format before making a tag query if you are not sure. You can have all tags used in the corpus for a given language listed – see the column Tags in the corpus in the table above. Or in a page displaying results open the View/Corpus-specific settings… menu to check the tag option in the Positional attributes box and choose the for each token option in the Viewing options box.

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\$”.

Structural attributes

StructureAttributeDescriptionValues
docdoc.iddocument identifier author's_last_name-shortened_title / _ACQUIS / _EUROPARL / _PRESSEUROP_year / _SUBTITLES / _SYNDICATE_year / _OT / _NT
texttext.idtext identifierauthor's_last_name-shortened_title:0 / _ACQUIS:number / _EUROPARL:number / _PRESSEUROP:number / _SUBTITLES:number / _SYNDICATE_year:name / _OT:book / _NT:book
text.authorauthorlast name, first name
text.titlefull titletext
text.langlanguagear / 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 / rn / ro / ru / sk / sl / sq / sr / sv / sy / tr / uk / vi / zh
text.versionversionnumber
text.groupcore/collection Core / Acquis / Europarl / PressEurop / Subtitles / Syndicate / Bible
text.publisherpublishertext
text.pubplacepublication placetext
text.pubDateYearpublication yearnumber
text.pubDateMonthpublication monthnumber
text.origyearoriginal creation yearnumber
text.isbnISBNnumber
text.txtypetext typediscussions - transcripts / drama / fiction / journalism - commentaries / journalism - news / legal texts / nonfiction / other / poetry / subtitles / religious
text.commentcommenttext
text.originaloriginal version?Yes / No
text.srclanglanguage of the originalar / 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 / rn / ro / ru / se / sk / sl / sq / sr / sv / ta / th / ti / tl / tr / tu / uk / un / ur / vi / zh
text.translatortranslatorlast name, first name
text.transsextranslator's genderF / M
text.authsexauthor's genderF / M
text.transcommenttranslation commenttext
text.collectiontitlecollection titletext
text.volumevolume numbernumber
text.pagesnumber of pagesnumber
text.lang_varlanguage varietyde-AT / de-CH / de-DE / en-AU / en-CA / en-GB / en-UM / en-US / es-ES / es-MX / es-PE / fr-BE / fr-FR / it-CH / it-IT / nl-BE / nl-NL / pt-BR / pt-PT / sr-RS
text.wordcountnumber of wordsnumber
divdiv.iddivision identifier (Bible) _NT / _OT:chapter
div.typedivision typechapter
pp.idparagraph identifierdoc:text:div:par
ss.idsentence identifierdoc:text:div:par:sent
hihi.rendtypefaceitalic / bold / bold italic
lblb.idverse identifier (Bible)book:chapter:verse

Acknowledgements

We are grateful for the possibility to use the following texts and software:

Texts:

Pre-processing

  • Parallel text editor InterText by Pavel Vondřička
  • Aligner Hunalign
  • Sentence splitter for Czech by Pavel Květoň
  • Sentence splitter for Norwegian by Jarle Ebeling and Pavel Vondřička
  • Sentence splitter Punkt for all other languages from Natural Language Toolkit

Taggers/lemmatizers:

See also

1)
Insert languages actually used.
2)
Ljubešić, N., Klubička, F., Željko Agić, and Jazbec, I.-P. (2016). New inflectional lexicons and training corpora for improved morphosyntactic annotation of Croatian and Serbian. In Calzolari, N. et al., editors, Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), Paris, France. European Language Resources Association (ELRA).
3)
Ljubešić, N. and Erjavec, T. (2016). Corpus vs. lexicon supervision in morphosyntactic tagging: the case of Slovene. In Calzolari, N. et al., editors, Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), Paris, France. European Language Resources Association (ELRA).