# 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 =
label.chooseResultsLocation = Choose result location
button.chooseResultsLocation = Set location
label.selectReader = Select reader
label.outputName = Output file name
label.corpusTab.chooseCorpusLocationH = Select the folder which contains the corpus. The folder should only contain one corpus and should not contain files that are not part of the corpus.
label.corpusTab.readHeaderInfoH = If you select this option, the taxonomy will be read separately. This might take a while.
label.corpusTab.chooseResultsLocationH = Choose result location
label.corpusTab.selectReaderH = Select reader
label.corpusTab.outputNameH = Output file name
# character analysis tab
label.stringLength = Number of characters
label.calculateFor = Calculate for
label.displayTaxonomy = Display taxonomies
label.dataLimit = Data limitations
label.msd = Morphosyntactic tag
label.taxonomy = Filter by taxonomy
label.minimalOccurrences = Min. nr. occurrences
label.minimalTaxonomy = Min. nr. tax. branches
label.minimalRelFre = Min. rel. frequency
label.taxonomySetOperation = Filtriraj taksonomijo po
label.solarFilters = Selected filters:
string.lemma = lemma
string.word = word
label.letter.stringLengthH = Enter the length of character strings.
label.letter.calculateForH = Character strings will be counted in the selected units.
label.letter.displayTaxonomyH = The output will also contain the distribution of character strings across the corpus taxonomy.
label.letter.msdH = Character strings will be counted only in words with the provided tag.
label.letter.taxonomyH = Character strings will be counted only in selected text types.
label.letter.minimalOccurrencesH = Character strings with fewer occurrences will not be included in the output.
label.letter.minimalTaxonomyH = Character strings that occur in fewer taxonomy branches will not be included in the output.
label.letter.taxonomySetOperationH = Izpisuj iz besedil, ki ustrezajo vsaj eni od izbranih vej (unija) ali vsem izbranim vejam (presek)
# word part tab
label.alsoVisualize = Also split by
label.lengthSearch = Search for word parts of a specified length
label.prefixLength = Length of initial part
label.suffixLength = Length of final part
label.listSearch = Search for word parts with a specified list
label.prefixList = List of initial parts
label.suffixList = List of final parts
label.wordPart.calculateForH = Word parts will be counted in the selected units.
label.wordPart.alsoVisualizeH = The output will also include the selected data.
label.wordPart.displayTaxonomyH = The output will also contain the distribution of word parts across the corpus taxonomy.
label.wordPart.prefixLengthH = Specify the length (in number of characters) of the initial word part.
label.wordPart.suffixLengthH = Specify the length (in number of characters) of the final word part.
label.wordPart.prefixListH = Separate the word parts with a semicolon (e.g. out; over)
label.wordPart.suffixListH = Separate the word parts with a semicolon (e.g. ation; ness).
label.wordPart.msdH = Word parts will only be counted in words with the specified tag.
label.wordPart.taxonomyH = Word parts will only be counted in the selected text types.
label.wordPart.minimalOccurrencesH = Units with the specified word part that occur fewer times will not be included in the output.
label.wordPart.minimalTaxonomyH = Units with the specified word part that are present in fewer taxonomy branches will not be included in the output.
label.wordPart.minimalRelFreH = Minimal relative frequency per million occurrences.
# word tab
label.writeMsdAtTheEnd = Split the morphosyntactic tag
label.word.calculateForH = Specify what the program should treat as the main unit for the output.
label.word.alsoVisualizeH = The output will also contain the selected data.
label.word.displayTaxonomyH = The output will also contain the distribution of units across the corpus taxonomy.
label.word.writeMsdAtTheEndH = The output will also include individual parts of morphosyntactic tags.
label.word.msdH = Only words with the specified tag will be counted.
label.word.taxonomyH = Only words in the selected text types will be counted.
label.word.minimalOccurrencesH = Words with fewer occurrences will not be included in the output.
label.word.minimalTaxonomyH = Words that occur in fewer taxonomy branches will not be included in the output.
# word sets tab
label.wordSet.calculateForH = Specify the units from which word sets will be extracted.
label.wordSet.alsoVisualizeH = The output will also include the selected data.
label.wordSet.displayTaxonomyH = The output will also contain the distribution of word sets across the corpus taxonomy.
label.wordSet.skipValueH = Enter the maximum number of words that can appear between two words in a word set.
label.wordSet.ngramValueH = The program will extract word sets with the specified number of tokens.
label.wordSet.notePunctuationsH = Word sets will include punctuation.
label.wordSet.collocabilityH = The program will also calculate collocability measures between words within the word set.
label.wordSet.msdH = The program will only count word sets with the specified tag.
label.wordSet.taxonomyH = Word sets will only be extracted from the selected taxonomy branches.
label.wordSet.minimalOccurrencesH = Word sets with fewer occurrences will not be included in the output.
label.wordSet.minimalTaxonomyH = Word sets that occur in fewer taxonomy branches will not be included in the output.
# calculate for
calculateFor.WORD = word
calculateFor.NORMALIZED_WORD = normalized word
calculateFor.LEMMA = lemma
calculateFor.MORPHOSYNTACTIC_SPECS = morphosyntactic tag
calculateFor.MORPHOSYNTACTIC_PROPERTY = morphosyntactic property
calculateFor.WORD_TYPE = word type
calculateFor.DIST_WORDS = word
calculateFor.DIST_LEMMAS = lemma
# n-grams
label.skipValue = Skip value
label.slowSpeedWarning = WARNING! USING THE ABOVE FILTER MAY DECREASE PROCESSING SPEED!
label.ngramValue = N-gram length
label.notePunctuations = Include punctuation
label.collocability = Collocability
# taxonomy set operations
taxonomySetOperation.UNION = union
taxonomySetOperation.INTERSECTION = intersection
# 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 = No suitable corpus files have been found in the selected directory.
message.WARNING_RESULTS_DIR_NOT_VALID = You do not have permission to access the selected directory.
message.WARNING_DIFFERING_NGRAM_LEVEL_AND_FILTER_TOKENS = The specified n-gram length and number of words do not match.
message.WARNING_DIFFERING_NGRAM_LEVEL_AND_FILTER_TOKENS_INFO = Choose another number or modify the filter.
message.WARNING_WORD_OR_LEMMA = Specify if you want to calculate statistics for words or lemmas.
message.WARNING_ONLY_NUMBERS_ALLOWED = Please enter a valid number.
message.WARNING_NUMBER_TOO_BIG = The entered number is larger than the number of taxonomy branches.
message.WARNING_MISMATCHED_NGRAM_AND_TOKENS_VALUES = The number for n-grams (%d) and number of tags included (%d) must match.
message.WARNING_MISSING_STRING_LENGTH = String length must be higher than 0. Length is set to default value (1).
message.WARNING_NO_TAXONOMY_FOUND = The program was unable to read the taxonomy from the corpus files. Please select another directory or a different corpus.
message.WARNING_NO_SOLAR_FILTERS_FOUND = The program was unable to read the filters from corpus files. Please select another location or a different corpus.
message.ERROR_WHILE_EXECUTING = An error occurred during program execution.
message.ERROR_WHILE_SAVING_RESULTS_TO_CSV = An error occurred while saving results.
message.ERROR_NOT_ENOUGH_MEMORY = Your memory is insufficient for analyzing such a large amount of data.
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 = Nr. of found files: %s
message.NOTIFICATION_CORPUS = Corpus: %s
message.NOTIFICATION_ANALYSIS_COMPLETED = Analysis complete. The results have been saved successfully.
message.NOTIFICATION_ANALYSIS_COMPLETED_NO_RESULTS = Analysis complete, but it was not possible to calculate statistics to match all the specified conditions.
message.RESULTS_PATH_SET_TO_DEFAULT = Save location is set to corpus location.
message.NOTIFICATION_ANALYSIS_CANCELED = The analysis was canceled.
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 = Searching for and analyzing 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 = The punctuation in sentences is included in the analysis.
message.TOOLTIP_readDisplayTaxonomyChB = The output file will include the distribution across the taxonomy branches.
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 = characters
exportHeader.analysis.wordParts = word parts
exportHeader.analysis.words = words
exportHeader.analysis.wordSets = word sets
exportHeader.numberLetters = Number of characters:
exportHeader.calculateFor = Calculate for:
exportHeader.alsoFilter = Also split by:
exportHeader.displayTaxonomies = Display taxonomy branches:
exportHeader.ngramLevel = N-gram level:
exportHeader.skipValue = Skip value:
exportHeader.notePunctuations = Include punctuation:
exportHeader.collocability = Collocability:
exportHeader.writeMSDAtTheEnd = Write tag at the end:
exportHeader.prefixLength = Initial part length:
exportHeader.suffixLength = Final part length:
exportHeader.prefixList = Initial part list:
exportHeader.suffixList = Final part list:
exportHeader.msd = Morphosyntactic tag:
exportHeader.taxonomy = Filter by taxonomy:
exportHeader.minOccurrences = Min. nr. occurrences:
exportHeader.minTaxonomies = Min. nr. taxonomy branches:
exportHeader.additionalFilters = Additional filters:
exportHeader.yes = yes
exportHeader.no = no
exportHeader.taxonomySetOperation = Filter taxonomy by:
# export table header translations
exportTable.skippedWords = Skipped words
exportTable.lettersSmall = Characters (lower case)
exportTable.wordsSmall = Lemma (lower case)
exportTable.wordBeginning = Initial part of the word
exportTable.wordEnding = Final part of the word
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 = character 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