Modified translations + Added note punctuations in OneWord

This commit is contained in:
2019-02-04 14:31:29 +01:00
parent 588ce7e15c
commit b8dee86c36
6 changed files with 185 additions and 151 deletions

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@@ -24,96 +24,96 @@ button.chooseResultsLocation=Set location
label.selectReader=Select reader
label.outputName=Output file name
label.corpusTab.chooseCorpusLocationH=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.
label.corpusTab.readHeaderInfoH=If you select this option taxonomy will be read separately. This might take a while.
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 letters
label.stringLength=Number of characters
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.msd=Morphosyntactic tag
label.taxonomy=Filter by taxonomy
label.minimalOccurrences=Min. nr. occurrences
label.minimalTaxonomy=Min. nr. tax. branches
label.taxonomySetOperation=Filtriraj taksonomijo po
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.
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 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.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=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.
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.
# word tab
label.writeMsdAtTheEnd=Razbij oblikoskladenjsko oznako
label.writeMsdAtTheEnd=Split the morphosyntactic tag
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.
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=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.
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=msd
calculateFor.MORPHOSYNTACTIC_PROPERTY=oblikoskladenjska lastnost
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=* USAGE OF PREVIOUS FILTER MAY DECREASE ANALYZING SPEED
label.ngramValue=N-gram level
label.notePunctuations=Note punctuations
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
@@ -135,20 +135,20 @@ 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.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
@@ -157,28 +157,28 @@ 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_FOUND_X_FILES=Nr. 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.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_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_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=Punctuations in sentences are included in analysis
message.TOOLTIP_readDisplayTaxonomyChB=Output file will include statistics over taxonomies as well.
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
@@ -189,27 +189,27 @@ exportHeader.corpus=Corpus:
exportHeader.date=Date:
exportHeader.executionTime=Execution time:
exportHeader.analysis=Analysis:
exportHeader.analysis.letters=letters
exportHeader.analysis.letters=characters
exportHeader.analysis.wordParts=word parts
exportHeader.analysis.words=words
exportHeader.analysis.wordSets=Word sets
exportHeader.numberLetters=Number of letters:
exportHeader.analysis.wordSets=word sets
exportHeader.numberLetters=Number of characters:
exportHeader.calculateFor=Calculate for:
exportHeader.alsoFilter=Also filter:
exportHeader.displayTaxonomies=Display taxonomies:
exportHeader.alsoFilter=Also split by:
exportHeader.displayTaxonomies=Display taxonomy branches:
exportHeader.ngramLevel=N-gram level:
exportHeader.skipValue=Skip value:
exportHeader.notePunctuations=Note punctuations:
exportHeader.notePunctuations=Include punctuation:
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.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
@@ -217,10 +217,10 @@ exportHeader.taxonomySetOperation=Filter taxonomy by:
# 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.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
@@ -235,7 +235,7 @@ exportTable.part.msd=msd:
exportTable.part.msdProperty=msd property:
exportTable.part.wordType=word type:
exportTable.part.letterSet=letter set
exportTable.part.letterSet=character set
exportTable.part.word2=word
exportTable.part.normalizedWord2=normalized word
exportTable.part.lemma2=lemma