Point 36 in DETERMINERs/articles is defined as: ‘the’ + adjectives in a noun phrase, to specify An iWeb search: the _JJ _NN 1 THE OTHER HAND 459204 2 THE BEST WAY 361919 3 THE ONLY WAY 263862 Chinese,Female,4,g That is the only way to avoid the noise disturbing me. 4 THE OTHER SIDE 258462 5 THE ONLY THING 254602 6 THE FEDERAL GOVERNMENT […]
Points 16 & 17 in DETERMINERS/demonstratives are the use of ‘these’ and ‘those’ with plural nouns. iWeb search for these|those _NN2 1 THESE THINGS 291847 2 THOSE THINGS 157643 3 THESE TERMS 141602 4 THESE GUYS 121511 5 THESE TYPES 109413 6 THESE ISSUES 102295 7 THESE QUESTIONS 96723 8 THESE CHANGES 91304 9 THESE […]
Point 4 in VERBS/prepositional A1 is defined as: limited range of prepositional verbs followed by noun or pronoun objects. The examples in the EGP: listen_VV0 to_II music_NN1 look_VVI after_II her_PPHO1 look_VVI for_IF mushrooms_NN2 Point 31 at B1 is the same as above except: “increasing range”. *There is no other higher-level for this. And really this […]
Point 28 in the category of DETERMINERS is defined as: increasing range of quantifying determiners with singular nouns (‘each’, ‘an’, ‘one’ and numbers) each|an|one _NN1 1 ONE THING 587964 2 AN EXAMPLE 440517 3 AN OPPORTUNITY 390589 4 AN EMAIL 364587 5 AN ISSUE 358269 6 AN AREA 254162 Pelic students: Female,3,w Earthquakes destroy everything in an area and stir up dust from the destruction . 7 […]
Point 22 in DETERMINERS is defined as: increasing range of quantifying determiners with plural nouns ‘all’, ‘both’, ‘a few’ In iWeb: all|both _NN2 1 BOTH SIDES 258617 2 ALL THINGS 222190 3 ALL KINDS 211611 4 ALL SORTS 173460 5 ALL AGES 156459 6 ALL STUDENTS 134399 7 ALL ASPECTS 131110 8 ALL TYPES 115579 […]
Point 35 in the category of NOUNS is defined as: prepositional phrase after the main noun in a noun phrase. We can roughly follow the EGP examples with the following code: _[AJD] _n _i _[AJD] _n (but iWeb doesn’t allow alternates in []) Also we have discovered as of 4/12/2020 that iWeb works better with […]
1 HISTORY (NN1) 3291043 2 STORY (NN1) 3184406 3 MEMORY (NN1) 1152441 4 THEORY (NN1) 854191 5 CATEGORY (NN1) 802465 6 VICTORY (NN1) 569542 7 FACTORY (NN1) 534302 8 DIRECTORY (NN1) 472252 9 INVENTORY (NN1) 433730 10 REGULATORY (JJ) 344896 11 TERRITORY (NN1) 335570 12 LABORATORY (NN1) 327694 13 GLORY (NN1) 290624 14 ADVISORY (JJ) […]
1 CHRISTIANS (NN2) 300655 2 PHYSICIANS (NN2) 274754 3 MUSICIANS (NN2) 225627 4 POLITICIANS (NN2) 211753 5 INDIANS (NN2) 167921 6 CANADIANS (NN2) 156879 7 TECHNICIANS (NN2) 129132 8 GUARDIANS (NN2) 99782 9 AUSTRALIANS (NN2) 98618 10 CIVILIANS (NN2) 92291 11 HISTORIANS (NN2) 81859 12 RUSSIANS (NN2) 71180 13 CLINICIANS (NN2) 62328 14 CORINTHIANS (NN2) […]
1 AUSTRALIAN (JJ) 710846 2 CANADIAN (JJ_NN1) 668799 3 CHRISTIAN (JJ) 576614 4 INDIAN (JJ) 427053 5 RUSSIAN (JJ) 400558 6 BRIAN (NP1) 365292 7 PHYSICIAN (NN1) 350753 8 ITALIAN (JJ_NN1) 322927 9 ASIAN (JJ) 261909 10 GUARDIAN (NN1) 213597 11 IAN (NP1) 180509 12 MUSICIAN (NN1) 135424 13 SYRIAN (JJ) 132610 14 VICTORIAN (JJ) […]
1 SPLIT (VVN) 88303 2 SPLIT (VVI) 85577 6 SPLIT (NN1) 26531 7 SPLIT (JJ) 17450 12 SPLIT (VVD) 9537 16 SPLIT (VV0) 7780