# 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
button.setCorpusLocation = Set corpus location
checkBox.readHeaderInfo = Read info from headers
button.chooseResultsLocation = Choose result location
# 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