Home > VocabProfilers
VocabProfile Home     *WITH*: Edit-to-Profile Facility (on BNC, BNL, Classic & Neoclassic - from Window input)

Classic VP Classic v.4 (English, JUNE 2013)
Laufer and Nation's classic four-way (GSL1/GSL2/AWL/OFFLIST) word sorter
Plus
*New!* Extractable user or technical list   + 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)

Variations & Updates

VP_COMPLEAT! With NEOCLASSIC OPTION (NGSL/NAWL) - 17 May 2014
  BNC-20 | BNC-COCA-25 + CORE-4 | BNL | NGSL/NAWL | FRENCH 5
  On 1 interface for clear comparisons  

Separate interfaces for    +   VP-kids  ||   + BNL     || + Classic

French VP_Fr v. 2.7 AUG 2013 v.3! An option in VP_Compleat

Archived
  • VP 1.2 (2003) French

Vocabulary Profilers break texts down by word frequencies in the language at large, as opposed to in the text itself. Most of the English Vocabprofilers on this site are based on Laufer and Nation's Lexical Frequency Profiler, and divide the words of texts into either first and second thousand levels, academic words, and the remainder or 'offlist,' or the BNC based 20 levels plus off-list. [Since this was written, several more frameworks have taken the field - see VP-Compleat.] VP is used for many research and teaching purposes (like matching text to learner via Levels Test   (click here to see how).

  New!   text_lex_compare   output
auto-links
to VP
Typical format     Sample output    

Integral 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]

Lexical Profilers adapted for Web by Tom Cobb, UQAM. Download latest offline version (Range) from Paul Nation or Lawrence Antony (ANT-Profiler).