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1 Technical Report Series on Corpus Building Vol. 2 (March 2013) Danish Corpora Uwe Quasthoff Dirk Goldhahn Erla Hallsteinsdóttir Abteilung Automatische Sprachverarbeitung, Institut für Informatik, Universität Leipzig

2 Affiliation oft the authors: Uwe Quasthoff und Dirk Goldhahn: Institut für Informatik,Universität Leipzig {quasthoff, Erla Hallsteinsdóttir, Institut for Sprog og Kommunikation, Syddansk Universitet Odense, Copyright: Abteilung Automatische Sprachverarbeitung, Institut für Informatik, Universität Leipzig, Technical Report Series on Corpus Building Vol. 1: Deutscher Wortschatz 2013 Vol. 2: Danish Corpora This PDF document was created using the open source tool mwlib. For more infotmation, see PDF generated at: Tue, 15 May :19:38 UTC

3 Danish corpora 1 Introduction to corpus creation 1 DAN - a processing related language description 2 DAN corpora 4 DAN corpus comparison 8 Processing details 10 Appendix to dan news 2007: Database summary 10 Appendix to dan news 2008: Database summary 10 Appendix to dan news 2010: Database summary 11 Appendix to dan news 2011: Database summary 11 Appendix to dan newscrawl 2011: Database summary 12 Appendix to dan wikipedia 2007: Database summary 12 Appendix to dan wikipedia 2012: Database summary 13 Appendix to dan web 2002: Database summary 13 Appendix to dan web 2011: Database summary 14 Appendix to dan mixed 2012: Database summary 14 Content details 15 Appendix to dan news 2007: Size of different TLDs 15 Appendix to dan news 2008: Size of different TLDs 15 Appendix to dan news 2010: Size of different TLDs 16 Appendix to dan news 2011: Size of different TLDs 16 Appendix to dan newscrawl 2011: Size of different TLDs 17 Appendix to dan web 2002: Size of different TLDs 17 Appendix to dan web 2011: Size of different TLDs 17 Appendix to dan mixed 2012: Size of different TLDs 18 Appendix to dan news 2007: Size of largest domains 18 Appendix to dan news 2008: Size of largest domains 19 Appendix to dan news 2010: Size of largest domains 19 Appendix to dan news 2011: Size of largest domains 20 Appendix to dan newscrawl 2011: Size of largest domains 21 Appendix to dan web 2002: Size of largest domains 21

4 Appendix to dan web 2011: Size of largest domains 22 Appendix to dan mixed 2012: Size of largest domains 22 Appendix to dan news 2007: Number of sources by time period 23 Appendix to dan news 2008: Number of sources by time period 24 Appendix to dan news 2010: Number of sources by time period 25 Appendix to dan news 2011: Number of sources by time period 26 Word details 28 Appendix to dan news 2007: Words by length without multiplicity 28 Appendix to dan news 2008: Words by length without multiplicity 30 Appendix to dan news 2010: Words by length without multiplicity 32 Appendix to dan news 2011: Words by length without multiplicity 34 Appendix to dan newscrawl 2011: Words by length without multiplicity 36 Appendix to dan wikipedia 2007: Words by length without multiplicity 38 Appendix to dan wikipedia 2012: Words by length without multiplicity 40 Appendix to dan web 2002: Words by length without multiplicity 42 Appendix to dan web 2011: Words by length without multiplicity 44 Appendix to dan mixed 2012: Words by length without multiplicity 46 Appendix to dan news 2007: Words by length with multiplicity 48 Appendix to dan news 2008: Words by length with multiplicity 50 Appendix to dan news 2010: Words by length with multiplicity 52 Appendix to dan news 2011: Words by length with multiplicity 54 Appendix to dan newscrawl 2011: Words by length with multiplicity 56 Appendix to dan wikipedia 2007: Words by length with multiplicity 58 Appendix to dan wikipedia 2012: Words by length with multiplicity 60 Appendix to dan web 2002: Words by length with multiplicity 62 Appendix to dan web 2011: Words by length with multiplicity 64 Appendix to dan mixed 2012: Words by length with multiplicity 66 Appendix to dan news 2007: The most frequent 50 words 67 Appendix to dan news 2008: The most frequent 50 words 68 Appendix to dan news 2010: The most frequent 50 words 69 Appendix to dan news 2011: The most frequent 50 words 70 Appendix to dan newscrawl 2011: The most frequent 50 words 71 Appendix to dan wikipedia 2007: The most frequent 50 words 72 Appendix to dan wikipedia 2012: The most frequent 50 words 73 Appendix to dan web 2002: The most frequent 50 words 74 Appendix to dan web 2011: The most frequent 50 words 75 Appendix to dan mixed 2012: The most frequent 50 words 76

5 Appendix to dan news 2007: Longest words in top by rank 77 Appendix to dan news 2008: Longest words in top by rank 78 Appendix to dan news 2010: Longest words in top by rank 79 Appendix to dan news 2011: Longest words in top by rank 80 Appendix to dan newscrawl 2011: Longest words in top by rank 81 Appendix to dan wikipedia 2007: Longest words in top by rank 82 Appendix to dan wikipedia 2012: Longest words in top by rank 83 Appendix to dan web 2002: Longest words in top by rank 84 Appendix to dan web 2011: Longest words in top by rank 85 Appendix to dan mixed 2012: Longest words in top by rank 86 Character details 87 Appendix to dan news 2007: Alphabet as used in the top words 87 Appendix to dan news 2008: Alphabet as used in the top words 88 Appendix to dan news 2010: Alphabet as used in the top words 90 Appendix to dan news 2011: Alphabet as used in the top words 91 Appendix to dan newscrawl 2011: Alphabet as used in the top words 92 Appendix to dan wikipedia 2007: Alphabet as used in the top words 94 Appendix to dan wikipedia 2012: Alphabet as used in the top words 95 Appendix to dan web 2002: Alphabet as used in the top words 96 Appendix to dan web 2011: Alphabet as used in the top words 98 Appendix to dan mixed 2012: Alphabet as used in the top words 99 Abbreviation details 101 Appendix to dan news 2007: Most frequent abbreviations 101 Appendix to dan news 2008: Most frequent abbreviations 102 Appendix to dan news 2010: Most frequent abbreviations 103 Appendix to dan news 2011: Most frequent abbreviations 104 Appendix to dan newscrawl 2011: Most frequent abbreviations 105 Appendix to dan wikipedia 2007: Most frequent abbreviations 106 Appendix to dan wikipedia 2012: Most frequent abbreviations 107 Appendix to dan web 2002: Most frequent abbreviations 108 Appendix to dan web 2011: Most frequent abbreviations 109 Appendix to dan mixed 2012: Most frequent abbreviations 110 Appendix to dan news 2007: Left neighbors of the full stop 111 Appendix to dan news 2008: Left neighbors of the full stop 112 Appendix to dan news 2010: Left neighbors of the full stop 113 Appendix to dan news 2011: Left neighbors of the full stop 114

6 Appendix to dan newscrawl 2011: Left neighbors of the full stop 115 Appendix to dan wikipedia 2007: Left neighbors of the full stop 116 Appendix to dan wikipedia 2012: Left neighbors of the full stop 117 Appendix to dan web 2002: Left neighbors of the full stop 118 Appendix to dan web 2011: Left neighbors of the full stop 119 Appendix to dan mixed 2012: Left neighbors of the full stop 120 Appendix to dan news 2007: Left neighbors of the full stop with additional internal full stops 121 Appendix to dan news 2008: Left neighbors of the full stop with additional internal full stops 122 Appendix to dan news 2010: Left neighbors of the full stop with additional internal full stops 123 Appendix to dan news 2011: Left neighbors of the full stop with additional internal full stops 124 Appendix to dan newscrawl 2011: Left neighbors of the full stop with additional internal full stops 125 Appendix to dan wikipedia 2007: Left neighbors of the full stop with additional internal full stops 126 Appendix to dan wikipedia 2012: Left neighbors of the full stop with additional internal full stops 127 Appendix to dan web 2002: Left neighbors of the full stop with additional internal full stops 128 Appendix to dan web 2011: Left neighbors of the full stop with additional internal full stops 129 Appendix to dan mixed 2012: Left neighbors of the full stop with additional internal full stops 130 Sentences details 131 Appendix to dan news 2007: Shortest sentences 131 Appendix to dan news 2008: Shortest sentences 132 Appendix to dan news 2010: Shortest sentences 134 Appendix to dan news 2011: Shortest sentences 135 Appendix to dan newscrawl 2011: Shortest sentences 137 Appendix to dan wikipedia 2007: Shortest sentences 138 Appendix to dan wikipedia 2012: Shortest sentences 140 Appendix to dan web 2002: Shortest sentences 141 Appendix to dan web 2011: Shortest sentences 143 Appendix to dan mixed 2012: Shortest sentences 144 Appendix to dan news 2007: Longest sentences 146 Appendix to dan news 2008: Longest sentences 148 Appendix to dan news 2010: Longest sentences 150 Appendix to dan news 2011: Longest sentences 152 Appendix to dan newscrawl 2011: Longest sentences 154 Appendix to dan wikipedia 2007: Longest sentences 156 Appendix to dan wikipedia 2012: Longest sentences 158 Appendix to dan web 2002: Longest sentences 160 Appendix to dan web 2011: Longest sentences 162 Appendix to dan mixed 2012: Longest sentences 164

7 Appendix to dan news 2007: Length of sentences in characters 166 Appendix to dan news 2008: Length of sentences in characters 167 Appendix to dan news 2010: Length of sentences in characters 168 Appendix to dan news 2011: Length of sentences in characters 169 Appendix to dan newscrawl 2011: Length of sentences in characters 170 Appendix to dan wikipedia 2007: Length of sentences in characters 171 Appendix to dan wikipedia 2012: Length of sentences in characters 172 Appendix to dan web 2002: Length of sentences in characters 173 Appendix to dan web 2011: Length of sentences in characters 174 Appendix to dan mixed 2012: Length of sentences in characters 175 Appendix to dan news 2007: Length of sentences in words 176 Appendix to dan news 2008: Length of sentences in words 177 Appendix to dan news 2010: Length of sentences in words 178 Appendix to dan news 2011: Length of sentences in words 179 Appendix to dan newscrawl 2011: Length of sentences in words 180 Appendix to dan wikipedia 2007: Length of sentences in words 181 Appendix to dan wikipedia 2012: Length of sentences in words 182 Appendix to dan web 2002: Length of sentences in words 183 Appendix to dan web 2011: Length of sentences in words 184 Appendix to dan mixed 2012: Length of sentences in words 185 Oddities details 186 Appendix to dan news 2007: Longest words 186 Appendix to dan news 2008: Longest words 186 Appendix to dan news 2010: Longest words 187 Appendix to dan news 2011: Longest words 187 Appendix to dan newscrawl 2011: Longest words 188 Appendix to dan wikipedia 2007: Longest words 188 Appendix to dan wikipedia 2012: Longest words 189 Appendix to dan web 2002: Longest words 189 Appendix to dan web 2011: Longest words 190 Appendix to dan mixed 2012: Longest words 190 Appendix to dan news 2007: Sentences with high average word length 191 Appendix to dan news 2008: Sentences with high average word length 192 Appendix to dan news 2010: Sentences with high average word length 193 Appendix to dan news 2011: Sentences with high average word length 194 Appendix to dan newscrawl 2011: Sentences with high average word length 195 Appendix to dan wikipedia 2012: Sentences with high average word length 196

8 Appendix to dan news 2007: Problems with sentence segmentation - words ending in a stopword 197 Appendix to dan news 2008: Problems with sentence segmentation - words ending in a stopword 197 Appendix to dan news 2010: Problems with sentence segmentation - words ending in a stopword 198 Appendix to dan news 2011: Problems with sentence segmentation - words ending in a stopword 199 Appendix to dan newscrawl 2011: Problems with sentence segmentation - words ending in a stopword 200 Appendix to dan wikipedia 2007: Problems with sentence segmentation - words ending in a stopword 201 Appendix to dan wikipedia 2012: Problems with sentence segmentation - words ending in a stopword 201 Appendix to dan web 2002: Problems with sentence segmentation - words ending in a stopword 202 Appendix to dan web 2011: Problems with sentence segmentation - words ending in a stopword 203 Appendix to dan mixed 2012: Problems with sentence segmentation - words ending in a stopword 204

9 1 Danish corpora Introduction to corpus creation The Leipzig Corpora Collection (LCC) collects Web based corpora for many different languages. The main text genres are newspaper texts, Wikipedias and randomly collected web pages. All corpora are processed in the same way: Crawling Web pages HTML stripping Language identifikation Sentence segmentation Cleaning: Removal of ill-formed sentences Duplicate removal Calculation of word frequences and word co-occurrences As result we have a corpus containing only well-formed sentences in the language under consideration. The sentences are in random order; hence, sharing the corpus does not violate copyright law because it is impossible to reconstruct the original texts. The pre-processing steps contain both language independent steps (like HTML stripping and duplicate removal) and language dependent steps (like language identification and sentence segmentation). Especially the language specific parts are vulnerable to specific processing problems. The aim of the paper is to identify possible problems and evaluate the results. The following problems are adressed: A processing-focused language description Language size: How much text is available for this language? What are the biggest sources? Corpus description: Genre, size, crawling and processing date. Possible problems in language identification: Which languages are similar? Character set and alphabet Inspecting the word list: Most frequent words, longer high frequent words and longest words at all. Word length distribution. Can abbreviations confuse sentence segmentation? Information about the abbreviation list. Inspecting sentences: Inspect shortest and longest sentences to identify possible segmentation problems. Sentence length distribution. The paper describes the result of these inspections; the appendices show the exact results for the different corpora. This helps to compare the corpora with respect to quality. In the section quality overview, an overall quality description for each corpus is given. All corpora contain only minor problems which are irrelevant for most applications. Otherwise the corpus creation has been iterated.

10 DAN - a processing related language description 2 DAN - a processing related language description General properties of the Danish language Native Name: Dansk Classifiation: Indo-European, Germanic, North, East Scandinavian, Danish-Swedish, Danish-Riksmal, Danish Total Number of Speakers: 5.6M Largest countries with number of spakers: Denmark (5.6M) Source: / www. dst. dk/ en/ Statistik/ emner/ befolkning-og-befolkningsfremskrivning/ folketal. aspx Processing summary latin alphabet with some additional characters full stop is used as sentence boundary and for abbreviations apostrostophes used rarely Properties important for processing Alphabet and punctuation The alphabet is latin based, with the following specialities (sources: / en. wikipedia. org/ wiki/ Alphabets_derived_from_the_Latin and / en. wikipedia. org/ wiki/ Danish_and_Norwegian_alphabet): Danish includes all 26 base letters and Æ, Ø, Å Additional letter forms: É (a diacritic used for disamgiguation: en/et - én/ét) In foreign words: Á, À, Â, Ä, É, È, Ê, Ë, Í, Ì, Î, Ï, Ó, Ò, Ô, Ö, Ú, Ù, Û, Ü and more Additional digraphs: EE in foreign words (trainee, frisbee); AA in older texts (replaced by å in 1948) and names (Aalborg, Aarhus). NB! Aa is treetet like Å in alphabetical sorting in danish words only, meaning that Aabenraa is listet under Å (last letter of the alphabet) and Aachen under A. Å, Æ and Ø might occur as AA, AE and OE in newer texts (avoidance of language specific letters) Usual latin punctuation Usage of uppercase letters: At sentence beginnings and for proper names (of persons, organisations, countries etc.). When a word beginning with Aa is capitalized, only the first letter becomes capital, e.g. Aarhus. Sentence segmentation and word tokenization Sentence beginnings Sentences begin with a capitalized first word. Abbreviations Abbreviations confusing with sentence boundaries: Special abbreviation list has to be inspected. Sources for abbreviations: / www. dsn. dk/ retskrivning/ retskrivningsregler/ a / a / a7-42 and / www. dsn. dk/ sprogviden/ udgivelser/ sprognaevnets-skriftserie-1/ flere-udgivelser/ Rigtigt%20kort%20indskannet. pdf/ at_download/ file Abbreviations with full stop may appear in the word list without full stop. Apostrophes (http:// www. dsn. dk/ retskrivning/ retskrivningsregler/ a7-1-6/ a7-6)

11 DAN - a processing related language description 3 Use of apostrophes: infrequent. in elliptical forms like "bli'", "hva'", "ha'", "ka'" and "la'r" instead of "blive", "hvad", "have", "kan" and "lader" (Bitte überprüfen, warum nach "ha'" immer ein ";" steht, dies passt nicht) to mark combination of a word/radical and inflectional endings: in combination of definite article: euro'en, PC'en, SMS'erne, OP'ens, CD-ROM'en used to mark genitive (instead of "s") in words that end with the letters s, z or x: Marx's ven Wilhelm Liebknecht, Georg Brandes' Plads to mark a genitive or plural form with "s": Jan's, foto's (both incorrect but frequent usages), and, in certain cases, other inflectional endings on proper names: Albert'er (2x Albert), Alberte'r (2x Alberte), Borges'ske dimensioner, Crohn's sygdom in combination with english (or other foreign) words: chicken satay's, Google's brugsoplevelser to mark combination of numerals and inflectional endings: 60'er-rock to mark combination of foreign words ending on "-ee" and inflectional endings: frisbee'en, yankee'er Mainly used to mark citations Sources and ranking (2012) Estimated number of webpages containing text Google.com top-5 words: results for "i" "og" "at" "er" "på" Google.com top-10 words: results for "i" "og" "at" "er" "på" "til" "en" "af" "for" "med" Rank according to number of speakers (Ethnologue): 111 Rank according to Wikipedia size (see / de. wikipedia. org/ wiki/ Wikipedia:Sprachen): Rank 30 with articles. Rank according to number of newspapers as found by AbyZ (5/2012): 160 newspapers, rank 15. Rank according to number of newspapers with RSS feeds (5/2012): 110 newspapers, rank 14. Rank according to our corpus size (9/2012): 19

12 DAN corpora 4 DAN corpora Quality Overview Quality Ratings A: Very good quality. Ready to use (or already used) for frequency dictionary. Size as large as possible Only minimal errors Multiple genres (if possible) A-: Small problems identified. They should not affect usage. B: Native speaker quality. Information about abbreviations and sentence boundaries by native speaker Resulting statistics checked by native speaker, possible errors corrected C: Non-native speaker quality Obvious problems shown in corpus statistics are corrected D: First version Pre-processing with default abbreviation list and default sentence boundaries E: Poor Quality: Old, outdated or faulty. Corpus Quality The quality of the corpora differes slightly because the corpus processing toolchain changed slightly during several years. Moreover, original data are often no more available. Hence, improvement of quality often means removing incomplete or doubtful sentences. Forthcoming editions of all corpora thus might have a slightly smaller number of sentences. This especially applies to near duplicate sentences which are removed only sparingly. The following table shows the quality of the corpora. Minimal errors are still possible and described in the sections below. All possible major improvements are mentioned here. Corpus Quality rating Known problems to-dos dan_news_2007 A- near duplicates, see sentence length distibution - dan_news_2008 A - - dan_news_2010 A - - dan_news_2011 A - - dan_newscrawl_2011 A - - dan_wikipedia_2007 A- near duplicates, see sentence length distibution - dan_wikipedia_2012 A - - dan_web_2002 A - - dan_web_2011 A - - dan_mixed_2012 A - -

13 DAN corpora 5 Processing Overview For more details, see Appendix: Database Summary and Appendix: Number of sources by time period. Corpus Size (M sentences) Size (M running words) Multiwords Crawling date Production date dan_news_ / dan_news_ / dan_news_ / dan_news_ dayly dan_newscrawl_ batch crawling 2012 dan_wikipedia_ dump dan_wikipedia_ dump dan_web_ randomly dan_web_ randomly dan_mixed_ Content Overview For more details, see Appendix: Size of different TLDs and Appendix: Size of different domains. Corpus Type of sources Countries Number of sources Publishing date Biggest source dan_news_2007 News dk 42 newspapers dan_news_2008 News dk 56 newspapers dan_news_2010 News dk 45 newspapers dan_news_2011 News dk 36 newspapers dan_newscrawl_2011 News dk 73 newspapers 2011 and before dan_wikipedia_2007 Wikipedia dan_wikipedia_2012 Wikipedia dan_web_2002 Web dk domains 2002 and before dan_web_2011 Web dk domains 2011 and before aarhus.lokalavisen.dk/ dan_mixed_2012 combined combined domains 2011 and before Words Appendix: Words by Length without multiplicity and Appendix: Words by Length without multiplicity show the length distribution for words. The curves should be smooth and decreasing for length>=5. Appendix: The Most Frequent 50 Words shows the most frequent stopwords as well as one or more words related to the region. Appendix: Longest Words in Top-1000 by rank shows the 25 longest words within the top They usually give an impression of the main topics treated in the corpus. Appendix: Longest Words with minimum frequency 2 should give an idea of very long words. In the case of processing problems, different types of non-words may appear. This might help to improve the word definition.

14 DAN corpora 6 Corpus Word length graph without multiplicity Word length graph with multiplicity Most Frequent 50 Words Longest Words in Top-1000 Longest Words with minimum frequency 2 dan_news_2007 okay okay, min. avg okay okay URLs, routes dan_news_2008 okay okay okay okay okay dan_news_2010 okay okay okay okay URLs, routes dan_news_2011 okay okay okay okay missing blanks, hex strings dan_newscrawl_2011 okay okay Publiceret and.. okay URLs, routes, missing blanks dan_wikipedia_2007 okay, min. avg okay, max. avg okay okay URLs, routes dan_wikipedia_2012 okay okay okay okay URLs dan_web_2002 okay, max. avg okay okay okay missing blanks, special characters dan_web_2011 okay okay okay okay missing blanks, special characters dan_mixed_2012 okay okay okay okay all errors as above Remarks The average word length (without multiplicity) differs for the different text genres. There is an unexpected minimum in the length distribution (with multiplicity) for length 4. Abbreviations For sentence boundary detection, abbreviations ending in a full stop are of interest: Such abbreviations are usually not used as sentence boundaries. Conversely, missing abbreviations can overgenerate sentence boundaries. The list of abbreviations is of high quality: nearly complete and manually checked. Due to limitations in the processing chain, this list of abbreviations is only used for sentence boundary detection and not included in the word list. Hence, abbreviations ending with a full stop appear in the word list without the full stop. Sentences Appendix: Shortest sentences shows the shortest declarative, exclamatory and interrogative sentences. In preprocessing, a minimal length for sentences might be specified. And missing abbreviations are often visible as faulty sentence endings. Appendix: Longest sentences shows the longest declarative, exclamatory and interrogative sentences. Usually, the maximun sentence length is defined as 256 characters (not 256 bytes). Very long exclamatory or interrogative sentences often contain an overseen sentence boundary. Appendix: Length of sentences in characters shows the distribution of the sentence length. A large and balanced corpus will result in a smooth and bell-shaped curve. Isolated local maxima usually result from large sets of near duplicate sentences.

15 DAN corpora 7 Corpus Shortest sentences Longest sentences Length distribution (in characters) dan_news_2007 unsymmetric quotation marks okay near duplicate peak at 48 dan_news_2008 some unsymmetric quotation marks okay sentences longer than 255? dan_news_2010 okay 1 menu list, 2x hex data near duplicate peak at 42? Length distribution (in words) okay okay okay dan_news_2011 duplicate sentences declarative sentences with many time data near duplicate peak at 42 okay dan_newscrawl_2011 okay declarative sentences with many time data many near duplicate peaks many near duplicate peaks dan_wikipedia_2007 declarative sentences beginning with digits and ending with abbrev. okay near duplicate peak at 20 sharp maximum at 10 dan_wikipedia_2012 okay okay okay okay dan_web_2002 dan_web_2011 dan_mixed_2012 declarative non-sentences, interrogative sentences beginning lowercase or with blank Lowercase beginnings for declarative sentences okay very smooth okay Enumerations, multiple sentences max. 277 characters Oddities Appendix: Sentences with high average word length: Average sentences contain many stopwords, and these stopwords are usually short. Hence, they restrict the average word length in a sentence. Conversely, sentences with high average word length are often ill formed. They may be used to improve pre-processing. Appendix: Problems with sentence segmentation - Words ending in a stopword: If there are many ill-formed word or sentence boundaries witout a blank between two words, they will generate new ill-formed words. The appendix shows the most frequent words ending in an uppercase stopword. If they are infrequent then the date were of high quality. Corpus Sentences with high average word length Words ending in a stopword... dan_news_2007 all kinds of errors okay dan_news_2008 okay okay dan_news_2010 2x hex strings maxfreq=11 dan_news_2011 2x hex strings, 2x missing blanks maxfreq=24 dan_newscrawl_2011 1x missing blanks maxfreq=805 dan_wikipedia_2007 (no data) okay dan_wikipedia_2012 okay maxfreq=27 dan_web_2002 missing blanks, underscores maxfreq=67 dan_web_2011 missing blanks maxfreq=58 dan_mixed_2012 missing blanks, underscores words containing ";"

16 DAN corpus comparison 8 DAN corpus comparison Automated Corpus comparison For the conducted comparisons, the following tests on the top-1000 words are performed: Vectors based on the frequencies of the top-1000 words are created for the analysed languages. As similarity value, 1-cos(alpha) of the angle alpha between these vectors is computed. Identical languages receive a value of 0, distinct languages get a value of 1. The same analysis is conducted using the frequencies of the top-1000 typical letter trigrams of the languages. Monolingual word list comparison (top-1000 words) As one can expect the comparisons show: The different news corpora have word lists with maximum distance 0.19 (dan_newscrawl_2011 and dan_news_2008) The web corpora have word lists with distance 0.13 The wikipedia corpora are similar with distance 0.10 The biggest distance of 0.36 can be found between dan_wikipedia_2007 dan_news_2008 The mixed corpus dan_mixed_2012 has a central position within the corpora and has a maximum distance of 0.31 to the wikipedia_2007 corpus Multilingual word list comparison (top-1000 words) Both the comparison of the top-1000 words and the comparison of the letter trigrams used in these words were conducted to find the most similar languages based on these features. The distance of Danish to the next languages considering words is 0.47 to Swedish. Considering letter trigrams the nearest language with distance 0.38 is Bokmål. These distances are below average. On average the value for the most similar language to a language in question is 0.58 for trigrams. The most similar languages based on words: Swedish, Bokmål, Nynorsk source language_short_name language_name cos_logfreq dan swe Swedish dan nob Norwegian, Bokmål dan nno Norwegian, Nynorsk dan fao Faroese dan isl Icelandic The most similar languages based on letter trigrams: Bokmål, Swedish, Dutch source language_short_name language_name cos_logfreq dan nob Norwegian, Bokmål dan swe Swedish dan nld Dutch dan nno Norwegian, Nynorsk

17 DAN corpus comparison 9 dan deu German

18 10 Processing details Appendix to dan news 2007: Database summary Values for some general parameters Parameter Value Number of sentences Number of running word forms Number of distinct word forms Number of multiwords 0 Percentage of words with frequency= Number of sentence based co-occurrences Number of neighbour co-occurrences Appendix to dan news 2008: Database summary Values for some general parameters Parameter Value Number of sentences Number of running word forms Number of distinct word forms Number of multiwords Percentage of words with frequency= Number of sentence based co-occurrences Number of neighbour co-occurrences

19 Appendix to dan news 2010: Database summary 11 Appendix to dan news 2010: Database summary Values for some general parameters Parameter Value Number of sentences Number of running word forms Number of distinct word forms Number of multiwords 9696 Percentage of words with frequency= Number of sentence based co-occurrences Number of neighbour co-occurrences Appendix to dan news 2011: Database summary Values for some general parameters Parameter Value Number of sentences Number of running word forms Number of distinct word forms Number of multiwords Percentage of words with frequency= Number of sentence based co-occurrences Number of neighbour co-occurrences

20 Appendix to dan newscrawl 2011: Database summary 12 Appendix to dan newscrawl 2011: Database summary Values for some general parameters Parameter Value Number of sentences Number of running word forms Number of distinct word forms Number of multiwords Percentage of words with frequency= Number of sentence based co-occurrences Number of neighbour co-occurrences Appendix to dan wikipedia 2007: Database summary Values for some general parameters Parameter Value Number of sentences Number of running word forms Number of distinct word forms Number of multiwords Percentage of words with frequency= Number of sentence based co-occurrences Number of neighbour co-occurrences

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