Appendix - Effect of cumulatively removing properties Table 1: Effect of cumulatively removing properties, trigram similarity threshold σ = 0.835, Reuters-21578, d = 2, Prefix: dbpedia-owl. Property Accuracy

Source URL: titan.informatik.uni-leipzig.de

Appendix - Algorithm for expansion policy Algorithm 1: Search candidates for named entities and expansion policy Data: N = {N1 , N2Nn } sorted in ascending order of their string length, trigram similarity threshol

Source URL: titan.informatik.uni-leipzig.de

Adding Context Information to Part Of Speech Tagging for Dialogues Sandra Kübler, Matthias Scheutz, Eric Baucom, Ross Israel Indiana University Bloomington, IN, USA {skuebler,mscheutz,eabaucom,raisrael}@indiana.edu

Source URL: cl.indiana.edu

• Linguistics
• Natural language processing
• Corpus linguistics
• Economy
• Markov models
• Computational linguistics
• Part-of-speech tagging
• Word-sense disambiguation
• Statistical natural language processing
• Tagger
• Trigram tagger
• Treebank

9. KONFERENCA JEZIKOVNE TEHNOLOGIJE Informacijska družba - IS 2014 9th Language Technologies Conference Information Society - IS 2014

Source URL: nl.ijs.si

• Computational linguistics
• Computing
• Linguistics
• Applied linguistics
• Named-entity recognition
• TimeML
• SemEval
• Temporal expressions
• Part-of-speech tagging
• Natural language processing
• Question answering
• Trigram tagger

Fast Domain Adaptation for Part of Speech Tagging for Dialogues ¨ Sandra Kubler, Eric Baucom Indiana University {skuebler,eabaucom}@indiana.edu

Source URL: cl.indiana.edu

• Linguistics
• Natural language processing
• Corpus linguistics
• Computational linguistics
• Applied linguistics
• Part-of-speech tagging
• Word-sense disambiguation
• Tagger
• Treebank
• Trigram tagger
• Parsing
• International Corpus of English

Aug25 A VOCABARET SPECIAL BY ADRIAN HOAD-REDDICK   Complete the clued words and phrases, each of which contains the trigram ‘AUG’. This birthday special has

Source URL: vocabaret.files.wordpress.com

POS Tagging for German: How Important is the Right Context? ¨ Steliana Ivanova, Sandra Kubler Umbria Inc., Boulder, CO, Indiana University Bloomington, IN, USA , Abstract

Source URL: cl.indiana.edu

• Markov models
• Computational linguistics
• Corpus linguistics
• Natural language processing
• Part-of-speech tagging
• Word-sense disambiguation
• Tagger
• Part of speech
• Tag
• Hidden Markov model
• Brill tagger
• Trigram tagger

Developing A Real-Word Spelling Corrector Based on Dickinson, Brew, & MeurersSpring 2015 Warning: this activity may cause you to think numerically. 1. We’ve talked about n-grams for language processing techniqu

Source URL: cl.indiana.edu

• Computational linguistics
• Natural language processing
• Speech recognition
• Language modeling
• Corpus linguistics
• N-gram
• Trigram
• Yin and yang
• Probability

20% About [Name] as told to Ucaoimhu by Mary Magdalene Horowitz Remember how in the movie All About Steve, I was so crazy about that lovable, strong, centered, divine male I completely messed up a crossword I was writing

Source URL: www.math.uchicago.edu

• Crosswords
• Puzzles
• Cryptic crossword
• Alphabetical
• Trigram
• -gry puzzle

Parsing German: How Much Morphology Do We Need? Wolfgang Maier Heinrich-Heine-Universit¨at D¨usseldorf D¨usseldorf, Germany

Source URL: cl.indiana.edu

• Corpus linguistics
• Computational linguistics
• Part-of-speech tagging
• Word-sense disambiguation
• Constraint Grammar
• Treebank
• Trigram tagger
• Tagger
• Plural
• Parsing
• Dependency grammar
• Syntax