# general
window.title=Corpus analyzer

hyperlink.help=Help
button.language=SL
button.computeNgrams=Calculate
button.cancel=Cancel

# template
tab.corpusTab=Corpus
tab.filterTab=Filter
tab.characterLevelTabNew=Characters
tab.wordLevelTab=Word parts
tab.oneWordAnalysisTab=Words
tab.stringLevelTabNew2=Word sets

# corpus tab
label.setCorpusLocation=Set corpus location
button.setCorpusLocation=Set location
label.readHeaderInfo=Read info from headers
checkBox.readHeaderInfo=Read info from headers
label.chooseResultsLocation=Choose result location
button.chooseResultsLocation=Set location
label.selectReader=Select reader
label.outputName=Output file name

# character analysis tab
label.stringLength=Number of letters
label.calculateFor=Calculate for
label.displayTaxonomy=Display taxonomies
label.dataLimit=Data limitations
label.msd=MSD
label.taxonomy=Taxonomy
label.minimalOccurrences=Min. n. occurrences
label.minimalTaxonomy=Min. n. taxonomies
label.solarFilters=Selected filters:
string.lemma=lemma
string.word=word

label.letter.stringLengthH=Enter length of letter output.
label.letter.calculateForH=Črkovni nizi bodo prešteti v izbranih enotah.
label.letter.displayTaxonomyH=Izpisana bo tudi razporeditev črkovnih nizov po taksonomiji korpusa.
label.letter.msdH=Črkovni nizi bodo prešteti samo v besedah z določeno oznako.
label.letter.taxonomyH=Črkovni nizi bodo prešteti samo v izbranih vrstah besedil.
label.letter.minimalOccurrencesH=Črkovni nizi z manj pojavitvami ne bodo vključeni v izpis.
label.letter.minimalTaxonomyH=Črkovni nizi, prisotni v manj taksonomskih vejah, ne bodo vključeni v izpis.

# word part tab
label.alsoVisualize=Also filter
label.lengthSearch=Search for word parts through specified length
label.prefixLength=Prefix length
label.suffixLength=Suffix length
label.listSearch=Search for word parts through specified prefixes and suffixes
label.prefixList=Prefix list
label.suffixList=Suffix list

label.wordPart.calculateForH=Besedni deli bodo prešteti v izbranih enotah.
label.wordPart.alsoVisualizeH=V izpis bodo vključeni tudi izbrani podatki.
label.wordPart.displayTaxonomyH=Izpisana bo tudi razporeditev besednih delov po taksonomiji korpusa.
label.wordPart.prefixLengthH=
label.wordPart.suffixLengthH=Določite dolžino (v številu črk) začetnega in/ali končnega dela besede.
label.wordPart.prefixListH=
label.wordPart.suffixListH=Besedne dele, ki jih želite iskati, ločite z vejico (npr. pre, raz).
label.wordPart.msdH=Besedni deli bodo prešteti samo v besedah z določeno oznako.
label.wordPart.taxonomyH=Besedni deli bodo prešteti samo v izbranih vrstah besedil.
label.wordPart.minimalOccurrencesH=Enote z iskanim besednim delom, ki se pojavijo redkeje, ne bodo vključene v izpis.
label.wordPart.minimalTaxonomyH=Enote z iskanim besednim delom, ki so prisotne v manj vejah, ne bodo vključene v izpis.

# word tab
label.writeMsdAtTheEnd=Razbij oblikoskladenjsko oznako

label.word.calculateForH=Določite, kaj naj program izpisuje kot glavno enoto.
label.word.alsoVisualizeH=V izpis bodo vključeni tudi izbrani podatki.
label.word.displayTaxonomyH=Izpisana bo tudi razporeditev enot po taksonomiji korpusa.
label.word.writeMsdAtTheEndH=Izpisani bodo tudi posamezni deli oblikoskladenjskih oznak.
label.word.msdH=Preštete bodo samo besede z določeno oznako.
label.word.taxonomyH=Besede bodo preštete samo v izbranih vrstah besedil.
label.word.minimalOccurrencesH=Besede, ki se pojavijo redkeje, ne bodo vključene v izpis.
label.word.minimalTaxonomyH=Besede, ki so prisotne v manj vejah, ne bodo vključene v izpis.

# word sets tab
label.wordSet.calculateForH=Določite, iz katerih enot bodo izpisani nizi.
label.wordSet.alsoVisualizeH=V izpis bodo vključeni tudi izbrani podatki.
label.wordSet.displayTaxonomyH=Izpisana bo tudi razporeditev besednih nizov po taksonomiji korpusa.
label.wordSet.skipValueH=Vnesite največje število besed, ki se lahko pojavijo med dvema besedama v nizu.
label.wordSet.ngramValueH=Program bo izpisal nize z izbranim številom pojavnic.
label.wordSet.notePunctuationsH=V besedne nize bodo vključena tudi ločila.
label.wordSet.collocabilityH=Izračunana bo tudi stopnja povezovalnosti med besedami v nizu glede na izbrane mere.
label.wordSet.msdH=Prešteti bodo samo besedni nizi z določeno oznako.
label.wordSet.taxonomyH=Besedni nizi bodo izpisani samo iz izbranih taksonomskih vej.
label.wordSet.minimalOccurrencesH=Besedni nizi, ki se pojavijo redkeje, ne bodo vključeni v izpis.
label.wordSet.minimalTaxonomyH=Besedni nizi, ki so prisotni v manj vejah, ne bodo vključeni v izpis.

# calculate for
calculateFor.WORD=word
calculateFor.NORMALIZED_WORD=normalized word
calculateFor.LEMMA=lemma
calculateFor.MORPHOSYNTACTIC_SPECS=msd
calculateFor.MORPHOSYNTACTIC_PROPERTY=oblikoskladenjska lastnost
calculateFor.WORD_TYPE=word type
calculateFor.DIST_WORDS=word
calculateFor.DIST_LEMMAS=lemma

# n-grams
label.skipValue=Skip value
label.slowSpeedWarning=* USAGE OF PREVIOUS FILTER MAY DECREASE ANALYZING SPEED
label.ngramValue=N-gram level
label.notePunctuations=Note punctuations
label.collocability=Collocability

# filtersSolar
filter.solarRegijaL=Region
filter.solarPredmetL=Subject
filter.solarRazredL=Class
filter.solarLetoL=Year
filter.solarSolaL=School
filter.solarVrstaBesedilaL=Text type
filter.solarRegija=region
filter.solarPredmet=subject
filter.solarRazred=class
filter.solarLeto=year
filter.solarSola=school
filter.solarVrstaBesedila=type

# messages
message.WARNING_CORPUS_NOT_FOUND=In selected directory there are no suitable corpus files.
message.WARNING_RESULTS_DIR_NOT_VALID=You don't have correct permissions to access chosen directory.
message.WARNING_DIFFERING_NGRAM_LEVEL_AND_FILTER_TOKENS=Selected ngram level and number of entered words do not match.
message.WARNING_DIFFERING_NGRAM_LEVEL_AND_FILTER_TOKENS_INFO=Choose other number or modify filter.
message.WARNING_WORD_OR_LEMMA=Choose, if you want to calculate statistics for words or lemmas.
message.WARNING_ONLY_NUMBERS_ALLOWED=Please enter valid number.
message.WARNING_NUMBER_TOO_BIG=Entered number is bigger than the number of taxonomies.
message.WARNING_MISMATCHED_NGRAM_AND_TOKENS_VALUES=Number for n-gram (%d) and number of msds included (%d) must match.
message.WARNING_MISSING_STRING_LENGTH=String length must be higher than 0. Length is set up at default value (1).
message.WARNING_NO_TAXONOMY_FOUND=We were unable to read taxonomy from corpus files. Please select other location or different corpus.
message.WARNING_NO_SOLAR_FILTERS_FOUND=We weren't able to read filters from corpus files. Please select other location or different corpus.
message.ERROR_WHILE_EXECUTING=Error in program execution.
message.ERROR_WHILE_SAVING_RESULTS_TO_CSV=Error while saving results.
message.ERROR_NOT_ENOUGH_MEMORY=You do not have sufficient RAM for analyzing such amount of data. You can try changing filters.
message.ERROR_NO_REGI_FILE_FOUND=Missing file \"%s\".

message.MISSING_NGRAM_LEVEL=N-gram level
message.MISSING_CALCULATE_FOR=Calculate for
message.MISSING_SKIP=""
message.MISSING_STRING_LENGTH=String length
message.MISMATCHED_STRING_LENGTH_AND_MSD_REGEX=String length and regex filter do not match.

message.NOTIFICATION_FOUND_X_FILES=Num. of found files: %s
message.NOTIFICATION_CORPUS=Corpus: %s
message.NOTIFICATION_ANALYSIS_COMPLETED=Analysis completed. Results are saved successfully.
message.NOTIFICATION_ANALYSIS_COMPLETED_NO_RESULTS=Analysis completed, however no statistics created that would match filters.
message.RESULTS_PATH_SET_TO_DEFAULT=Save location is set on corpus location.
message.NOTIFICATION_ANALYSIS_CANCELED=Analysis was cancled.

message.ONGOING_NOTIFICATION_ANALYZING_FILE_X_OF_Y=Analyzing file %d of %d (%s) - Estimated time remaining %d s
message.CANCELING_NOTIFICATION=Canceled

message.LABEL_CORPUS_LOCATION_NOT_SET=Corpus location is not set
message.LABEL_RESULTS_LOCATION_NOT_SET=Result location is not set
message.LABEL_RESULTS_CORPUS_TYPE_NOT_SET=Corpus type is not set.

message.LABEL_SCANNING_CORPUS=Search and analysis of corpus files...
message.LABEL_SCANNING_SINGLE_FILE_CORPUS=Input analysis
message.COMPLETED=Completed

message.TOOLTIP_chooseCorpusLocationB=Select folder which contains corpus. The folder should only contain one corpus and should not contain too many files that are not part of corpus.
message.TOOLTIP_readHeaderInfoChB=If you select this option taxonomy will be read separately. This might take a while.
message.TOOLTIP_readNotePunctuationsChB=Punctuations in sentences are included in analysis
message.TOOLTIP_readDisplayTaxonomyChB=Output file will include statistics over taxonomies as well.

windowTitles.error=Error
windowTitles.warning=Warning
windowTitles.confirmation=Confirmation

# export header translations
exportHeader.corpus=Corpus:
exportHeader.date=Date:
exportHeader.executionTime=Execution time:
exportHeader.analysis=Analysis:
exportHeader.analysis.letters=letters
exportHeader.analysis.wordParts=word parts
exportHeader.analysis.words=words
exportHeader.analysis.wordSets=Word sets
exportHeader.numberLetters=Number of letters:
exportHeader.calculateFor=Calculate for:
exportHeader.alsoFilter=Also filter:
exportHeader.displayTaxonomies=Display taxonomies:
exportHeader.ngramLevel=N-gram level:
exportHeader.skipValue=Skip value:
exportHeader.notePunctuations=Note punctuations:
exportHeader.collocability=Collocability:
exportHeader.writeMSDAtTheEnd=Write MSD at the end:
exportHeader.prefixLength=Prefix length:
exportHeader.suffixLength=Suffix length:
exportHeader.prefixList=Prefix list:
exportHeader.suffixList=Suffix list:
exportHeader.msd=MSD:
exportHeader.taxonomy=Taxonomy:
exportHeader.minOccurrences=Min. n. occurrences:
exportHeader.minTaxonomies=Min. n. taxonomies:
exportHeader.additionalFilters=Additional filters:
exportHeader.yes=yes
exportHeader.no=no

# export table header translations
exportTable.skippedWords=Skipped words
exportTable.lettersSmall=Letters (small letters)
exportTable.wordsSmall=Lemma (small letters)
exportTable.wordBeginning=Word beginning
exportTable.wordEnding=Word ending
exportTable.wordRest=The rest of the word
exportTable.totalRelativeFrequency=Total relative frequency (over one million occurrences)
exportTable.absoluteFrequency=Absolute frequency
exportTable.percentage=Share
exportTable.relativeFrequency=Relative frequency
exportTable.msd=msd
# parts
exportTable.part.word=words:
exportTable.part.normalizedWord=normalized words:
exportTable.part.lemma=lemmas:
exportTable.part.msd=msd:
exportTable.part.msdProperty=msd property:
exportTable.part.wordType=word type:

exportTable.part.letterSet=letter set
exportTable.part.word2=word
exportTable.part.normalizedWord2=normalized word
exportTable.part.lemma2=lemma
exportTable.part.msd2=msd
exportTable.part.msdProperty2=msd property
exportTable.part.wordType2=word type

exportTable.part.letterSet2=Share of total sum of all letter sets
exportTable.part.letterSet3=Letter set
exportTable.part.word3=Word
exportTable.part.normalizedWord3=Normalized word
exportTable.part.lemma3=Lemma
exportTable.part.msd3=Msd
exportTable.part.msdProperty3=Msd property
exportTable.part.wordType3=Word type

exportTable.part.set=set
exportTable.part.share=Absolute share of
exportTable.part.absoluteFrequency=Absolute frequency of
exportTable.part.totalFound=Total sum of all
exportTable.part.totalFoundLetters=Total sum of all found letters of
exportTable.part.totalSumString=Total sum of
exportTable.part.totalSumLetters=Total sum of all letters of

# generated files names
exportFileName.letters=letters
exportFileName.wordParts=word-parts
exportFileName.words=words
exportFileName.wordSets=word-sets
exportFileName.gram=-gram
exportFileName.skip=-skip