Technical Report Series on Corpus Building

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1 Technical Report Series on Corpus Building Vol. 5 (April 2013) Hungarian Corpora Uwe Quasthoff Dirk Goldhahn Zita Hollós Abteilung Automatische Sprachverarbeitung, Institut für Informatik, Universität Leipzig

2 Affiliation of the authors: Uwe Quasthoff, Dirk Goldhahn: Institut für Informatik,Universität Leipzig {quasthoff, Zita Hollós: Károli Gáspár Református Egyetem (Budapest), Copyright: Abteilung Automatische Sprachverarbeitung, Institut für Informatik, Universität Leipzig, Technical Report Series on Corpus Building Vol. 1: Deutscher Wortschatz 2013 Vol. 2: Danish Corpora Vol. 3: Dutch Corpora Vol. 4: Icelandic Corpora Vol. 5: Hungarian Corpora This PDF document was created using the open source tool mwlib. For more infotmation, see PDF generated at: Tue, 15 May 2013

3 Hungarian corpora 1 Introduction to corpus creation 1 HUN - a processing related language description 2 HUN corpora 4 HUN corpus comparison 8 Processing details 10 Appendix to hun news 2007: Database summary 10 Appendix to hun news 2008: Database summary 10 Appendix to hun news 2009: Database summary 11 Appendix to hun news 2010: Database summary 11 Appendix to hun news 2011: Database summary 12 Appendix to hun newscrawl 2011: Database summary 12 Appendix to hun wikipedia 2007: Database summary 13 Appendix to hun wikipedia 2012: Database summary 13 Appendix to hun web 2003: Database summary 14 Appendix to hun web 2011: Database summary 14 Appendix to hun mixed 2012: Database summary 15 Content details 16 Appendix to hun news 2007: Size of different TLDs 16 Appendix to hun news 2008: Size of different TLDs 16 Appendix to hun news 2009: Size of different TLDs 17 Appendix to hun news 2010: Size of different TLDs 17 Appendix to hun news 2011: Size of different TLDs 17 Appendix to hun newscrawl 2011: Size of different TLDs 18 Appendix to hun web 2003: Size of different TLDs 18 Appendix to hun web 2011: Size of different TLDs 18 Appendix to hun mixed 2012: Size of different TLDs 19 Appendix to hun news 2007: Size of largest domains 19 Appendix to hun news 2008: Size of largest domains 20 Appendix to hun news 2009: Size of largest domains 20 Appendix to hun news 2010: Size of largest domains 21

4 Appendix to hun news 2011: Size of largest domains 22 Appendix to hun newscrawl 2011: Size of largest domains 22 Appendix to hun web 2003: Size of largest domains 23 Appendix to hun web 2011: Size of largest domains 23 Appendix to hun mixed 2012: Size of largest domains 24 Appendix to hun news 2007: Number of sources by time period 25 Appendix to hun news 2008: Number of sources by time period 26 Appendix to hun news 2009: Number of sources by time period 27 Appendix to hun news 2010: Number of sources by time period 28 Appendix to hun news 2011: Number of sources by time period 30 Word details 32 Appendix to hun news 2007: Words by length without multiplicity 32 Appendix to hun news 2008: Words by length without multiplicity 34 Appendix to hun news 2009: Words by length without multiplicity 36 Appendix to hun news 2010: Words by length without multiplicity 38 Appendix to hun news 2011: Words by length without multiplicity 40 Appendix to hun newscrawl 2011: Words by length without multiplicity 42 Appendix to hun wikipedia 2007: Words by length without multiplicity 44 Appendix to hun wikipedia 2012: Words by length without multiplicity 46 Appendix to hun web 2003: Words by length without multiplicity 48 Appendix to hun web 2011: Words by length without multiplicity 50 Appendix to hun mixed 2012: Words by length without multiplicity 52 Appendix to hun news 2007: Words by length with multiplicity 54 Appendix to hun news 2008: Words by length with multiplicity 56 Appendix to hun news 2009: Words by length with multiplicity 58 Appendix to hun news 2010: Words by length with multiplicity 60 Appendix to hun news 2011: Words by length with multiplicity 62 Appendix to hun newscrawl 2011: Words by length with multiplicity 64 Appendix to hun wikipedia 2007: Words by length with multiplicity 66 Appendix to hun wikipedia 2012: Words by length with multiplicity 68 Appendix to hun web 2003: Words by length with multiplicity 70 Appendix to hun web 2011: Words by length with multiplicity 72 Appendix to hun mixed 2012: Words by length with multiplicity 74 Appendix to hun news 2007: The most frequent 50 words 75 Appendix to hun news 2008: The most frequent 50 words 76 Appendix to hun news 2009: The most frequent 50 words 77 Appendix to hun news 2010: The most frequent 50 words 78

5 Appendix to hun news 2011: The most frequent 50 words 79 Appendix to hun newscrawl 2011: The most frequent 50 words 80 Appendix to hun wikipedia 2007: The most frequent 50 words 81 Appendix to hun wikipedia 2012: The most frequent 50 words 82 Appendix to hun web 2003: The most frequent 50 words 83 Appendix to hun web 2011: The most frequent 50 words 84 Appendix to hun mixed 2012: The most frequent 50 words 85 Appendix to hun news 2007: Longest words in top by rank 86 Appendix to hun news 2008: Longest words in top by rank 87 Appendix to hun news 2009: Longest words in top by rank 88 Appendix to hun news 2010: Longest words in top by rank 89 Appendix to hun news 2011: Longest words in top by rank 90 Appendix to hun newscrawl 2011: Longest words in top by rank 91 Appendix to hun wikipedia 2007: Longest words in top by rank 92 Appendix to hun wikipedia 2012: Longest words in top by rank 93 Appendix to hun web 2003: Longest words in top by rank 94 Appendix to hun web 2011: Longest words in top by rank 95 Appendix to hun mixed 2012: Longest words in top by rank 96 Character N-gram details 97 Appendix to hun news 2007: Alphabet as used in the top words 97 Appendix to hun news 2008: Alphabet as used in the top words 98 Appendix to hun news 2009: Alphabet as used in the top words 99 Appendix to hun news 2010: Alphabet as used in the top words 101 Appendix to hun news 2011: Alphabet as used in the top words 102 Appendix to hun newscrawl 2011: Alphabet as used in the top words 103 Appendix to hun wikipedia 2007: Alphabet as used in the top words 105 Appendix to hun wikipedia 2012: Alphabet as used in the top words 106 Appendix to hun web 2003: Alphabet as used in the top words 107 Appendix to hun web 2011: Alphabet as used in the top words 109 Appendix to hun mixed 2012: Alphabet as used in the top words 110 Abbreviation details 112 Appendix to hun news 2007: Most frequent abbreviations 112 Appendix to hun news 2008: Most frequent abbreviations 113 Appendix to hun news 2009: Most frequent abbreviations 114 Appendix to hun news 2010: Most frequent abbreviations 115 Appendix to hun news 2011: Most frequent abbreviations 116

6 Appendix to hun newscrawl 2011: Most frequent abbreviations 117 Appendix to hun wikipedia 2007: Most frequent abbreviations 118 Appendix to hun wikipedia 2012: Most frequent abbreviations 119 Appendix to hun web 2003: Most frequent abbreviations 120 Appendix to hun web 2011: Most frequent abbreviations 121 Appendix to hun mixed 2012: Most frequent abbreviations 122 Appendix to hun news 2007: Left neighbors of the full stop 123 Appendix to hun news 2008: Left neighbors of the full stop 124 Appendix to hun news 2009: Left neighbors of the full stop 125 Appendix to hun news 2010: Left neighbors of the full stop 126 Appendix to hun news 2011: Left neighbors of the full stop 127 Appendix to hun newscrawl 2011: Left neighbors of the full stop 128 Appendix to hun wikipedia 2007: Left neighbors of the full stop 129 Appendix to hun wikipedia 2012: Left neighbors of the full stop 130 Appendix to hun web 2003: Left neighbors of the full stop 131 Appendix to hun web 2011: Left neighbors of the full stop 132 Appendix to hun mixed 2012: Left neighbors of the full stop 133 Appendix to hun news 2007: Left neighbors of the full stop with additional internal full stops 134 Appendix to hun news 2008: Left neighbors of the full stop with additional internal full stops 135 Appendix to hun news 2009: Left neighbors of the full stop with additional internal full stops 136 Appendix to hun news 2010: Left neighbors of the full stop with additional internal full stops 137 Appendix to hun news 2011: Left neighbors of the full stop with additional internal full stops 138 Appendix to hun newscrawl 2011: Left neighbors of the full stop with additional internal full stops 139 Appendix to hun wikipedia 2007: Left neighbors of the full stop with additional internal full stops 140 Appendix to hun wikipedia 2012: Left neighbors of the full stop with additional internal full stops 141 Appendix to hun web 2003: Left neighbors of the full stop with additional internal full stops 142 Appendix to hun web 2011: Left neighbors of the full stop with additional internal full stops 143 Appendix to hun mixed 2012: Left neighbors of the full stop with additional internal full stops 144 Sentences details 145 Appendix to hun news 2007: Shortest sentences 145 Appendix to hun news 2008: Shortest sentences 146 Appendix to hun news 2009: Shortest sentences 148 Appendix to hun news 2010: Shortest sentences 149 Appendix to hun news 2011: Shortest sentences 151 Appendix to hun newscrawl 2011: Shortest sentences 152 Appendix to hun wikipedia 2007: Shortest sentences 154

7 Appendix to hun wikipedia 2012: Shortest sentences 155 Appendix to hun web 2003: Shortest sentences 157 Appendix to hun web 2011: Shortest sentences 158 Appendix to hun mixed 2012: Shortest sentences 160 Appendix to hun news 2007: Longest sentences 161 Appendix to hun news 2008: Longest sentences 163 Appendix to hun news 2009: Longest sentences 165 Appendix to hun news 2010: Longest sentences 167 Appendix to hun news 2011: Longest sentences 169 Appendix to hun newscrawl 2011: Longest sentences 171 Appendix to hun wikipedia 2007: Longest sentences 173 Appendix to hun wikipedia 2012: Longest sentences 175 Appendix to hun web 2003: Longest sentences 177 Appendix to hun web 2011: Longest sentences 179 Appendix to hun mixed 2012: Longest sentences 181 Appendix to hun news 2007: Length of sentences in characters 183 Appendix to hun news 2008: Length of sentences in characters 184 Appendix to hun news 2009: Length of sentences in characters 185 Appendix to hun news 2010: Length of sentences in characters 186 Appendix to hun news 2011: Length of sentences in characters 187 Appendix to hun newscrawl 2011: Length of sentences in characters 188 Appendix to hun wikipedia 2007: Length of sentences in characters 189 Appendix to hun wikipedia 2012: Length of sentences in characters 190 Appendix to hun web 2003: Length of sentences in characters 191 Appendix to hun web 2011: Length of sentences in characters 192 Appendix to hun mixed 2012: Length of sentences in characters 193 Appendix to hun news 2007: Length of sentences in words 194 Appendix to hun news 2008: Length of sentences in words 195 Appendix to hun news 2009: Length of sentences in words 196 Appendix to hun news 2010: Length of sentences in words 197 Appendix to hun news 2011: Length of sentences in words 198 Appendix to hun newscrawl 2011: Length of sentences in words 199 Appendix to hun wikipedia 2007: Length of sentences in words 200 Appendix to hun wikipedia 2012: Length of sentences in words 201 Appendix to hun web 2003: Length of sentences in words 202 Appendix to hun web 2011: Length of sentences in words 203 Appendix to hun mixed 2012: Length of sentences in words 204

8 Oddities details 205 Appendix to hun news 2007: Longest words 205 Appendix to hun news 2008: Longest words 205 Appendix to hun news 2009: Longest words 206 Appendix to hun news 2010: Longest words 206 Appendix to hun news 2011: Longest words 207 Appendix to hun newscrawl 2011: Longest words 207 Appendix to hun wikipedia 2007: Longest words 208 Appendix to hun wikipedia 2012: Longest words 208 Appendix to hun web 2003: Longest words 209 Appendix to hun web 2011: Longest words 209 Appendix to hun mixed 2012: Longest words 210 Appendix to hun news 2007: Sentences with high average word length 210 Appendix to hun news 2008: Sentences with high average word length 211 Appendix to hun news 2009: Sentences with high average word length 212 Appendix to hun news 2010: Sentences with high average word length 213 Appendix to hun news 2011: Sentences with high average word length 214 Appendix to hun newscrawl 2011: Sentences with high average word length 216 Appendix to hun wikipedia 2007: Sentences with high average word length 217 Appendix to hun wikipedia 2012: Sentences with high average word length 218 Appendix to hun web 2003: Sentences with high average word length 219 Appendix to hun web 2011: Sentences with high average word length 220 Appendix to hun mixed 2012: Sentences with high average word length 221 Appendix to hun news 2007: Problems with sentence segmentation - words ending in a stopword 222 Appendix to hun news 2008: Problems with sentence segmentation - words ending in a stopword 223 Appendix to hun news 2009: Problems with sentence segmentation - words ending in a stopword 224 Appendix to hun news 2010: Problems with sentence segmentation - words ending in a stopword 224 Appendix to hun news 2011: Problems with sentence segmentation - words ending in a stopword 225 Appendix to hun newscrawl 2011: Problems with sentence segmentation - words ending in a stopword 226 Appendix to hun wikipedia 2007: Problems with sentence segmentation - words ending in a stopword 227 Appendix to hun wikipedia 2012: Problems with sentence segmentation - words ending in a stopword 227 Appendix to hun web 2003: Problems with sentence segmentation - words ending in a stopword 228 Appendix to hun web 2011: Problems with sentence segmentation - words ending in a stopword 229 Appendix to hun mixed 2012: Problems with sentence segmentation - words ending in a stopword 230

9 1 Hungarian 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 HUN - a processing related language description 2 HUN - a processing related language description General properties of the language Native Name: Magyar Classifiation: Uralic Total Number of Speakers: 12.5M Largest countries with number of spakers: Hungary (9.5M), Romania (1.5M), Serbia (0.5M), Slovakia (0.5M) Source: / www. ethnologue. org/ show_language. asp?code=hun Processing summary latin alphabet with some additional characters full stop is used as sentence boundary and for abbreviations apostrostophes used very rarely Properties important for processing Alphabet and punctuation Alphabet: A Á B C Cs D Dz Dzs E É F G Gy H I Í J K L Ly M N Ny O Ó Ö Ő P (Q) R S Sz T Ty U Ú Ü Ű V (W) (X) (Y) Z Zs Characters in parentheses appear only in loanwords and proper names. The digraphs and trigraphs above are considered as single letters. Usual latin punctuation Source: / de. wikipedia. org/ wiki/ Ungarische_Sprache#Alphabet Due to keybord limitations, some authors use incorrect alternativ characters: ô and õ instead of ő (up to 10% each) û instead of ű (up to 20%) Usage of uppercase letters: At sentence beginnings and for proper names. Titles like doktor are often written in lowercase.

11 HUN - a processing related language description 3 Sentence segmentation and word tokenization Abbreviations Abbreviations confusing with sentence boundaries: Special abbreviation list. Has to be cleaned. Sources for abbreviations: Machine generated / ZH Abbreviations with full stop may appear in the word list without full stop. Apostrophes Use of apostrophes: Very rare in foreign proper names. Frequency ratio compared with comma in hun_newscrawl_2011: '/, = / Multiwords Number of multiwords: sources: Wikipedia For a list of some high frequent multiwords, see Appendix 1: Statscript applied to hun_mixed_2012 Sources and ranking (2012) Estimated number of webpages containing text Google.com top-5 words: 261,000,000 results for "az" "és" "A" "hogy" "is" Google.com top-10 words: 61,300,000 results for "az" "és" "A" "hogy" "is" "nem" "Az" "egy" "meg" "volt" Rank according to number of speakers (Ethnologue): 61 Rank according to Wikipedia size ( , see / de. wikipedia. org/ wiki/ Wikipedia:Sprachen): Rank 19 with articles. Rank according to number of newspapers as found by AbyZ (2012): 90 newspapers, rank 23 Rank according to number of newspapers with RSS feeds (2012): 102 newspapers, rank 15 Rank according to our corpus size (5/2012): 8

12 HUN corpora 4 HUN 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 REMARK FOR EDITORS: THIS TABLE WILL BE FILLED IN THE LAST STEP SUMMARIZING ALL OTHER RESULTS. Due to keybord limitations, some authors use incorrect alternativ characters within words. Corpus Quality rating Known problems to-dos hun_news_2007 B top-50 words not clean, maximal sentence length problem - hun_news_2008 A- top-50 words not clean - hun_news_2009 A- top-50 words not clean - hun_news_2010 A- top-50 words not clean - hun_news_2011 A- top-50 words not clean - hun_newscrawl_2011 A- top-50 words not clean - hun_wikipedia_2007 A- top-50 words not clean - hun_wikipedia_2010 A- top-50 words not clean - hun_web_2003 A- top-50 words not clean - hun_web_2011 A- top-50 words not clean - hun_mixed_2012 A- top-50 words not clean -

13 HUN 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 hun_news_ daily 2007, mainly from May to December 2012 hun_news_ daily hun_news_ daily hun_news_ daily hun_news_ daily hun_newscrawl_ batch crawling hun_wikipedia_ dump hun_wikipedia_ dump hun_web_ (2002) 2007 hun_web_ randomly hun_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 hun_news_2007 News hu 39 newspapers hun_news_2008 News hu 78 newspapers hun_news_2009 News hu 82 newspapers hun_news_2010 News hu 68 newspapers hun_news_2011 News hu 59 newspapers 2011 hvg.hu hun_newscrawl_2011 News hu 66 newspapers 2011 and before hun_wikipedia_2007 Wikipedia and before wikipedia.org hun_wikipedia_2010 Wikipedia and before wikipedia.org hun_web_2003 Web hu unknown 2002 and before unknown hun_web_2011 Web hu, ro, sk, domains 2011 and before hun_mixed_2012 combined combined domains 2011 and before

14 HUN corpora 6 Words Appendix: Words by Length without multiplicity shows a plot of the corresponding length distribution. A smooth asymetric bell-shaped curve is expected. Appendix: Words by Length with multiplicity shows a plot of the corresponding length distribution. A smooth asymetric bell-shaped curve is expected. 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. 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 hun_news_2007 okay okay at rank 34 okay routes, Trojan-Downloader.Win32.Conhook.gen hun_news_2008 okay okay at rank 38 okay routes hun_news_2009 okay okay at rank 38 okay missing blanks, routes hun_news_2010 okay okay and included hun_news_2011 okay okay and included hun_newscrawl_2011 okay okay, and is. included hun_wikipedia_2007 okay okay and felhasználó(k included okay okay okay Wikipédia-felhasználó(k included missing blanks, routes missing blanks, routes missing blanks, routes routes hun_wikipedia_2010 okay okay included okay routes hun_web_2003 okay okay okay okay missing blanks, routes, special characters hun_web_2011 okay okay and is. included okay missing blanks, routes, special characters hun_mixed_2012 okay okay okay okay all above Abbreviations Abbreviations are usually not used as sentence boundaries. Conversely, missing abbreviations can overgenerate sentence boundaries. Due to limitations in the processing chain, the list of abbreviations used for sentence boundary detection can differ from the abbreviations in the word list. Appendix: Most Frequent Abbreviations shows possible under-generation of sentence boundaries by wrong abbreviations (i.e. words ending in a full stop) in the word list.

15 HUN corpora 7 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 engings. 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. Corpus Shortest sentences Longest sentences Length distribution (in characters) Length distribution (in words) hun_news_2007 okay char_length=249 too few long sentences, maximum 256 byte instead 256 characters okay hun_news_2008 okay okay okay okay hun_news_2009 okay okay okay okay hun_news_2010 okay okay okay okay hun_news_2011 okay okay okay okay hun_newscrawl_2011 okay okay okay okay hun_wikipedia_2007 okay okay okay okay hun_wikipedia_2010 okay okay okay okay hun_web_2003 okay okay okay okay hun_web_2011 okay okay okay okay hun_mixed_2012 okay okay okay okay 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.

16 HUN corpora 8 Corpus Sentences with high average word length Words ending in a stopword hun_news_2007 okay maxfreq=25 hun_news_2008 okay maxfreq=28 hun_news_2009 okay maxfreq=18 hun_news_2010 okay maxfreq=22 hun_news_2011 okay maxfreq=43 hun_newscrawl_2011 special characters included maxfreq=24 hun_wikipedia_2007 okay okay hun_wikipedia_2010 URLs in sentences okay hun_web_2003 missing blanks maxfreq=24 hun_web_2011 special characters, missing blanks maxfreq=10 hun_mixed_2012 all above maxfreq=64 POS Tagging HunPOS provides POS-Tagging and is used for Hungarian and Swedish. If applied to a corpus, frequencies for words with POS-tags are provided. HUN corpus comparison Automated Corpus comparison For the following 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. The cosine of the angle 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 different word lists with maximum distance 0.17 (hun_newscrawl_2011 und hun_news_2007) The wikipedia corpora are similar with maximum distance 0.12 The web corpora have distance 0.15 The mixed corpus hun_mixed_2012 holds a central position with maximum distances of 0.33 to the other corpora.

17 HUN corpus comparison 9 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 show that there is no similar language in our data. The distance of the mixed corpus to the next languages are 0.85 for the words and 0.85 for the letter trigrams. Both distances are so large that they do not represent similarity. On average the value for the most similar language is 0.58 for trigrams. The most similar languages based on words: Palauan, Konkani, Catalan-Valencian-Balear source language_short_name language_name cos_logfreq hun pau Palauan hun knn Konkani hun cat Catalan-Valencian-Balear hun ibo Igbo hun slk Slovak The most similar languages based on letter trigrams: Norwegian(Bokmål), Dutch, Palauan source language_short_name language_name cos_logfreq hun nob Norwegian, Bokmål hun nld Dutch hun pau Palauan hun bre Breton hun swe Swedish

18 10 Processing details Appendix to hun 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 8315 Percentage of words with frequency= Number of sentence based co-occurrences Number of neighbour co-occurrences Appendix to hun 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 hun news 2009: Database summary 11 Appendix to hun news 2009: 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 hun 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 Percentage of words with frequency= Number of sentence based co-occurrences Number of neighbour co-occurrences

20 Appendix to hun news 2011: Database summary 12 Appendix to hun 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 Appendix to hun 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

21 Appendix to hun wikipedia 2007: Database summary 13 Appendix to hun 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 Appendix to hun wikipedia 2012: 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

22 Appendix to hun web 2003: Database summary 14 Appendix to hun web 2003: 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 hun web 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

23 Appendix to hun mixed 2012: Database summary 15 Appendix to hun mixed 2012: 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

24 16 Content details Appendix to hun news 2007: Size of different TLDs TLDs larger than 1% TLD # of sources %.hu/ net/ Appendix to hun news 2008: Size of different TLDs TLDs larger than 1% TLD # of sources %.hu/ net/

25 Appendix to hun news 2009: Size of different TLDs 17 Appendix to hun news 2009: Size of different TLDs TLDs larger than 1% TLD # of sources %.hu/ net/ Appendix to hun news 2010: Size of different TLDs TLDs larger than 1% TLD # of sources %.hu/ com/ Appendix to hun news 2011: Size of different TLDs TLDs larger than 1% TLD # of sources %.hu/ com/

26 Appendix to hun newscrawl 2011: Size of different TLDs 18 Appendix to hun newscrawl 2011: Size of different TLDs TLDs larger than 1% TLD # of sources %.hu/ org/ com/ Appendix to hun web 2003: Size of different TLDs TLDs larger than 1% TLD # of sources %.hu/ Appendix to hun web 2011: Size of different TLDs TLDs larger than 1% TLD # of sources %.hu/ ro/ com/ sk/ eu/

27 Appendix to hun mixed 2012: Size of different TLDs 19 Appendix to hun mixed 2012: Size of different TLDs TLDs larger than 1% TLD # of sources %.hu/ org/ com/ Appendix to hun news 2007: Size of largest domains Largest domains Source # of sentences inforadio.hu/ vg.hu/ hvg.hu/ ma.hu/ nol.hu/ # of distinct sources 39

28 Appendix to hun news 2008: Size of largest domains 20 Appendix to hun news 2008: Size of largest domains Largest domains Source # of sentences nol.hu/ vg.hu/ inforadio.hu/ bulvar.ma.hu/ belfold.ma.hu/ eletmod.hu/ # of distinct sources 78 Appendix to hun news 2009: Size of largest domains Largest domains Source # of sentences inforadio.hu/ vg.hu/ bulvar.ma.hu/ belfold.ma.hu/ # of distinct sources 82

29 Appendix to hun news 2009: Size of largest domains 21 Appendix to hun news 2010: Size of largest domains Largest domains Source # of sentences hvg.hu/ vg.hu/ inforadio.hu/ vg.hu.feedsportal.com/ belfold.ma.hu/ prohardver.hu/ eletmod.hu/ # of distinct sources 68

30 Appendix to hun news 2011: Size of largest domains 22 Appendix to hun news 2011: Size of largest domains Largest domains Source # of sentences hvg.hu/ inforadio.hu/ vg.hu/ belfold.ma.hu/ webbulvar.hu/ kulfold.ma.hu/ # of distinct sources 59 Appendix to hun newscrawl 2011: Size of largest domains Largest domains Source # of sentences # of distinct sources 66

31 Appendix to hun newscrawl 2011: Size of largest domains 23 Appendix to hun web 2003: Size of largest domains Largest domains Source # of sentences mokk.bme.hu/ # of distinct sources 1 Appendix to hun web 2011: Size of largest domains Largest domains Source # of sentences # of distinct sources 33992

32 Appendix to hun mixed 2012: Size of largest domains 24 Appendix to hun mixed 2012: Size of largest domains Largest domains Source # of sentences mokk.bme.hu/ hvg.hu/ inforadio.hu/ vg.hu/ hu.wikipedia.org/ # of distinct sources 34112

33 Appendix to hun news 2007: Number of sources by time period 25 Appendix to hun news 2007: Number of sources by time period Number of sources by year, month, and day Number of sources per year year # of sources % Number of sources per month month # of sources %

34 Appendix to hun news 2008: Number of sources by time period 26 Appendix to hun news 2008: Number of sources by time period Number of sources by year, month, and day Number of sources per year year # of sources % Number of sources per month month # of sources %

35 Appendix to hun news 2008: Number of sources by time period Appendix to hun news 2009: Number of sources by time period Number of sources by year, month, and day Number of sources per year year # of sources % Number of sources per month

36 Appendix to hun news 2009: Number of sources by time period 28 month # of sources % Appendix to hun news 2010: Number of sources by time period Number of sources by year, month, and day

37 Appendix to hun news 2010: Number of sources by time period 29 Number of sources per year year # of sources % Number of sources per month month # of sources %

38 Appendix to hun news 2011: Number of sources by time period 30 Appendix to hun news 2011: Number of sources by time period Number of sources by year, month, and day Number of sources per year year # of sources % Number of sources per month month # of sources %

39 Appendix to hun news 2011: Number of sources by time period

40 32 Word details Appendix to hun news 2007: Words by length without multiplicity Percentage of words of fixed length in characters, counted without multiplicty Average word length word length percentage

41 Appendix to hun news 2007: Words by length without multiplicity

42 Appendix to hun news 2007: Words by length without multiplicity Appendix to hun news 2008: Words by length without multiplicity Percentage of words of fixed length in characters, counted without multiplicty Average word length word length percentage

43 Appendix to hun news 2008: Words by length without multiplicity

44 Appendix to hun news 2008: Words by length without multiplicity Appendix to hun news 2009: Words by length without multiplicity Percentage of words of fixed length in characters, counted without multiplicty Average word length word length percentage

45 Appendix to hun news 2009: Words by length without multiplicity

46 Appendix to hun news 2009: Words by length without multiplicity Appendix to hun news 2010: Words by length without multiplicity Percentage of words of fixed length in characters, counted without multiplicty Average word length word length percentage

47 Appendix to hun news 2010: Words by length without multiplicity

48 Appendix to hun news 2010: Words by length without multiplicity Appendix to hun news 2011: Words by length without multiplicity Percentage of words of fixed length in characters, counted without multiplicty Average word length word length percentage

49 Appendix to hun news 2011: Words by length without multiplicity

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51 Appendix to hun newscrawl 2011: Words by length without multiplicity

52 Appendix to hun newscrawl 2011: Words by length without multiplicity Appendix to hun wikipedia 2007: Words by length without multiplicity Percentage of words of fixed length in characters, counted without multiplicty Average word length word length percentage

53 Appendix to hun wikipedia 2007: Words by length without multiplicity

54 Appendix to hun wikipedia 2007: Words by length without multiplicity Appendix to hun wikipedia 2012: Words by length without multiplicity Percentage of words of fixed length in characters, counted without multiplicty Average word length word length percentage

55 Appendix to hun wikipedia 2012: Words by length without multiplicity

56 Appendix to hun wikipedia 2012: Words by length without multiplicity Appendix to hun web 2003: Words by length without multiplicity Percentage of words of fixed length in characters, counted without multiplicty Average word length word length percentage

57 Appendix to hun web 2003: Words by length without multiplicity

58 Appendix to hun web 2003: Words by length without multiplicity Appendix to hun web 2011: Words by length without multiplicity Percentage of words of fixed length in characters, counted without multiplicty Average word length word length percentage

59 Appendix to hun web 2011: Words by length without multiplicity

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61 Appendix to hun mixed 2012: Words by length without multiplicity

62 Appendix to hun mixed 2012: Words by length without multiplicity Appendix to hun news 2007: Words by length with multiplicity Percentage of words of fixed length in characters, counted with multiplicty Average word length word length percentage

63 Appendix to hun news 2007: Words by length with multiplicity

64 Appendix to hun news 2008: Words by length with multiplicity 56 Appendix to hun news 2008: Words by length with multiplicity Percentage of words of fixed length in characters, counted with multiplicty Average word length word length percentage

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