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Classic VP English v. 3
Laufer and Nation's classic four-way (GSL1/GSL2/AWL/OFFLIST) word sorter
Plus *New!* VP Negative
    See which k-words are not in your text
        [+ 1-word version]
        [+ Allied VP-CLOZE builder]

Archived
  • Web VP 1.0 (2001)
  • Web VP 1.5 (2003)

Experimental Variations

    BNC-20  |   VP-kids  |   BNL

French VP_Fr v. 2.7 proper nouns automated

Archived
  • VP 1.2 (2003) French

Vocabulary Profilers break texts down by word frequencies in the language at large. Most of the English web Vocabprofilers on this site are based on Laufer and Nation's Lexical Frequency Profiler, and divide the words of texts into first and second thousand levels, academic words, and the remainder or 'offlist.' VP is used for many research and teaching purposes (like matching text to learner via the Levels Test ).

 

   New!   text_lex_compare   auto-links to VP Upgrades Jan 2006     Sample output    

Output text: buck did not read the newspapers or he would have known that trouble was brewing not only for himself but for every tide water dog strong of muscle and with warm long hair from puget sound to san diego

Breakdown 

1k types: [families 27 : types 29 : tokens 31 ] and_[1] buck_[1] but_[1] did_[1] dog_[1] every_[1] for_[2] from_[1] have_[1] he_[1] himself_[1] known_[1] long_[1] newspapers_[1] not_[2] of_[1] only_[1] or_[1] read_[1] sound_[1] strong_[1] that_[1] the_[1] to_[1] trouble_[1] was_[1] water_[1] with_[1] would_[1]
2k types: [3:3:3] hair_[1] tide_[1] warm_[1]
OFF types: [ ?:5:5 ] brewing_[1] diego_[1] muscle_[1] puget_[1] san_[1]
Profilers adapted for Web by Tom Cobb, UQAM. Download latest offline version (Range) from Paul Nation.