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informatik ‚informatics‘ Establishing synsets lære ‚studies‘ bromatologi ‚nutrition science‘ fag ‚subject‘ samfundsfag ‚social studies‘ videnskab ‚science‘ datalogi ‚computer science‘
informatik ‚informatics‘ Establishing synsets lære ‚studies‘ bromatologi ‚nutrition science‘ fag ‚subject‘ samfundsfag ‚social studies‘ One synset videnskab ‚science‘ datalogi ‚computer science‘
Page 1 and 2: DanNet From Dictionary to Wordnet J
Page 3 and 4: • • • DanNet Lexical-semantic
Page 5 and 6: 1. Introduction Outline 2. Characte
Page 7 and 8: • • • • Den Danske Ordbog W
Page 9 and 10: Semantic description Systematic dom
Page 11 and 12: Semantic description Hyperonym
Page 13 and 14: Semantic description Collocational
Page 15 and 16: Semantic description
Page 19: Homonymy & polysemy celle ‚cell
Page 23 and 24: Example: Hyponymy? kirsebærtræ
Page 26 and 27: Building the hierarchy TOP genstand
Page 28 and 29: Building the hierarchy TOP genstand
Page 30 and 31: • • Coding relations What is do
Page 32 and 33: Extraction of telic role fjernsyn
Page 34 and 35: Extraction of telic role fjernsyn
Page 36 and 37: Hypothesis
Page 38 and 39: Hypothesis Corpus query ‣ VPs in
Page 40 and 41: Results of corpus query query VP he
Page 42 and 43: Why this bad coverage?
Page 44 and 45: Why this bad coverage? 1. Definitio
Page 46 and 47: 1. GE that can VP-inf 2. GE that is
Page 48 and 49: A statistical approach
Page 50 and 51: • A statistical approach Frequenc
Page 52 and 53: • • A statistical approach Freq
Page 54 and 55: • • • • • • Some salien
Page 56 and 57: Automatic extraction?
Page 58 and 59: Automatic extraction? • Structura
Page 60 and 61: Automatic extraction? • ‣ ‣ S
Page 64 and 65: Cheap Expensive Conclusion Reusing
Page 66 and 67: Cheap Expensive Conclusion Reusing
Page 68 and 69: Conclusion The DanNet approach
Page 70 and 71:
Cheap Expensive Conclusion The DanN
Page 72:
Cheap Expensive Conclusion The DanN
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