Compleat Web VP v.2.1    NEW! million-word VPs (@ bottom)   Profile any text with *nine* list frameworks in *two* languages at *two* grain-sizes at *one* interface Note that BNL, Coca-Core, CEFR, and Classic AWL are not full 1000-family lists (see [?] details) and that NGSL and French are Lemmas not Families How to make list framework comparisons? Demo 8  here  Lex Frequency predicts Text Complexity? Check  these  Try VP Average-Level-sorted concordances. Easiest contexts first, check  this  VP-1 VP-Basic

➔ F R A M E W O R K S ➔

BNC-COCA 1-25k - [?]  Lists          > BNC-COCA 1-25 "c-series" (100 heads) [?]  Lists     CLASSIC (GSL/AWL) [?]  Lists    BNC 1-20k     [Fams Lems (15k)] [?]  Lists     BNC-COCA Core-4 [?]  Lists    NGSL +NAWL OR +TOEIC OR +BIZ [?]  Lists     CEFR - English [?]  Lists     BNL [?]  Lists     FRENCH v.5, 1-25k [?]  Lists

Input mode A Type or paste small to medium size text (max about 15,000 words) into window, choose options, and click yellow Submit_window button for Lexical Frequency Profile.
Title:  |+| Eng+Fr! Cognates (Lists)  |+| Sentence Count  |+| Bar Chart  |+| Coca Count-Index/List  ?   |+| Basic  ? 
INSTRUCTIONS: Type or paste your text here and click the yellow SUBMIT_window button. VocabProfile will tell you how many words the text contains from frequency bands as determined by analysing research corpora. For a demonstration, enter this text, or one of the sample texts below. TEXT SET-UP General: Include an empty space after every comma or full stop. Research: Deal with spelling errors and proper nouns. SIZE LIMITS: Web form input is currently max about 400,000 characters - use UPLOAD method below for larger files ( must be ~.txt; send in straight from your own hard drive). Text is NOT stored on Web VP's server
Demos: Isogram | Lit (1) (2) | Graded (1) (2) | Science (1) (2) | News (NYT) (WP) | Speech Adults Kids | Rex Murphy | Legal | GSL+AWL 1k 2K AWL | French      

➔ R E C A T

Words to recategorize => 1k (type or dbl-click) (E.g. known cognates/compounds)

PROPER NOUN HANDLING  ?  Mid-sentence capped words...  Treat as any text         *    Class as 1k/1c          *      Eliminate                   *

COMPOUNDS HANDLING  ?  When Off word is 2 wds...  Class as offlist  *    Break apart        * Texts to 2.5k; BNC-Coca

Plus propers at sentence boundary => 1k (E.g., ". Paul Martin")

Input mode B For large files,  to 1 million words >> LARGER TEXT = LESS RICH INFO >> FRAMEWORK IS BNC-COCA FAMS ONLY - OTHERS ON REQUEST

VP-BIG new! Brown Corpus (1 million) LOB Corpus (1 million) BNC Speech Sampler (900 thousand) BNC Writ. Sampler (>1 million) Graded 1k (500 thousand) TV Talk Corp. (500 thousand) War & Peace (600 thousand) Lady Chatterly (120 thousand) Great Gatsby (50 thousand) Call of the Wild (24 thousand)

UPLOAD LARGE TEXT FILE (with ~.txt file extension)