This system presents a letter and a digit as a humanoid animal; it also has humanoid animals to represent a digit and a letter.
I once designed a shorthand code system where a letter and a digit would mean a common word (or a digit and a letter would mean a common word). I thought that each letter could have an animal type such as a chimpanzee; and then digits 0 to 9 would have particular characteristics that need drawing over the template chimpanzee. So if I know that a chimpanzee is a particular letter, I can think of the characteristic of digit 5 and hopefully recall what the cartoon humanoid animal for that shorthand code is.
Time moved on and I decided to use a Women 1000 cartoon women system and a Male 1000 cartoon men system to represent shorthand codes instead. But I could see uses for the animal system. For instance, if at a peg loci location, I imagine a scene to represent the keyword "Industry", I could imagine the Hero system character that always means "IN" and that character can do the colpoured action that always means "DUS" and then, instead of using the "TR" hero [INDUSTR], I could add variety by imagining the recipient of the action to be the animal that means "TR". [T9 also means "TR" because of a translation rule where 9 always means "R".]; or for a longer word such as "Industrious", the action could be on the hero "TR" person but stood beside the action could be the animal "IO" character so that INDUSTRIO[us] is recalled.
For the case where a digit is followed by a letter, I don't have 10 characters for "digit and P" nor for "digit and H" nor for "digit and "M", K nor Q. So a future task will be to think up 10 images for M and P at least. They needn't be animal people and might actually be inanimate objects. I would just expect there to be times where a letter pair like "AP" or "SP" or "SM" would be wanted but I would not have an animal image for them. Besides, the Shorthand article assumes that I can combine a letter with a digit in order to represent two words of a sentence; and so that now has a gap! And the association of codes with people's names (as well as geographical landmarks) (see below) assumes that 0Q, 0K, etc. have images to represent them.
I will briefly comment on the animal images which either represent a 'letter then digit' or a 'digit then letter' (520 images in total).
Each letter of the alphabet is represented by an animal type such as a baboon. There can then be 10 colourful examples of a baboon as cartoon images to represent the 0 to 9 instances of a letter followed by a digit. The colour fill of the animal fur is not special - except that I tried to make variety by having each of the 10 occurrences of an animal breed have different colour fills.
Below are example cartoon images for representing a digit and letter or a letter and a digit [altohugh I changed the outfits since then]:




In the images, every animal is presented with humanoid aspects.
I want them to be able to do human-like actions; so I think it is OK to present them in a humanoid way. It will be very handy for when I want to memorise the three digit number of the 1000 actions articke because I can imagine a story where each animal does an action; and I can count through the animals quite simply because each animal type is a set of 10.
.Any animal code with a 0 will have an animal with chin beard, wrinkles to the side of the eyes. Any male animal with 1 in its code will be an animal with reddened ears. 2 = lines under the eyes. 3 = long eyelashes, 4 = chin beard, 5 = small moustache, 6 = facial hair on the cheeks, 7 = red eye lids, 8 = red spots on the cheeks, 9 = long hanging moustache
(For male animals (the animals whose code begins with a letter and ends with a digit)), that works ok; and I modified the system for females (any code beginning with a digit and ending with a letter) such that there are sunglasses or blusher or plain glasses or earrings rather than male facial hair [there is more about that below].
Using the animal people as a reduced AA-ZZ system
Instead of thinking of an animal as a letter and a digit (or a digit and then a letter), you could assign a letter to each digit so that two letters are represented.
Any letter from A to Z can have a second letter of A/E/I/O/U. Also, letters A/E/I/O/U can be followed by any letter from A to Z [in the same way that you can have A0 or 0A, there would be letter pair AO and letter pair OA expressed using different animal sets]. 0 = O, 1 = I, 2 = A, 3 = E, 4 = U ; 5 = N, 6 = S, 7 = C, 8 = T, 9 = R .
Animal A5 would be a prompt for syllable "AN" [5 stands in for 'N']. 5A would be a prompt for syllable "NA".
If, at a peg location, I already represented part of a foreign word's meaning by using an action; and part of the spelling by using a person as a recipient of the action, an addition to the scene can be an animal person to disclose an extra two letters.
Note: 'L' is a common letter which does not get represented by that approach. The digits here represent 5 vowels and 5 other common letters. As a future task, I would like to have extra images to mean common two letter uses of 'L' such as, AL, LL, etc..
Animal people as a way to memorise the 1000 actions
In the Actions article, I write about how the animal images having a count of about 500 makes them useful for remembering the ordinal position of either doers or recipients of actions.
I thought that I might reuse the same 500 animal people to represent 500 to 999: The direction of the action matters; so animal 300 acting from left to right is how I can memorise action 300; but if the action is from right to left (the animal faces leftwards) then I need to add 500 so that the action is thought of as action (300+500 = 800).
However, the 520 animal people system grew into a 600 character system where CH, SH, TH and ZH get treated as extra alphabet 'letters'. So you could have CH0, for instance; or 0CH. So then I can add just 400 characters to the list of doers in order to reach 1000 doers of actions.
The 100 People system from the 100 People for 00 to 99 article;
The Ancient Greece Dec 30th person as person 700 just to that the remaining use of Ancient Greece people are aligned nicely;
The 1st to the 10th of the month for January to October as seen in the Ancient Greece article;
The 11th to the 20th of the month for January to October as seen in the Ancient Greece article;
The 21st to the 30th of the month for January to October as seen in the Ancient Greece article [but February has no 30th; so use Jan 31st as a substitute].
I write more about this in the '1024 is 32 x 32' article. I wanted to extend the list of doer people to 1024; and that article is about how I extend it as well as about who the recipients of the actions are. E.g. 1001 to 1023 can use the Ancient Greece people for November 1st to November 23rd.
Animal people as first names
I made a list of first names (see below) so that an animal like animal A2 means a particular common first name. Since the prominent feature of some animal cartoons is a moustache or facial hair, some female names are oddly matched with masculine feature animals; so I would use:
If the name is feminine and there is a 4 or 5 or 6 or 9 in the digit-then-letter code:
4 - beard -> sunglasses
5 - small moustache -> blusher on the cheeks (red colour or blue if the animal is red-skinned)
6 - facial hair -> square glasses
9 - long moustache -> white diamond shape ear rings
Eg. Pushpa is 4W. The 4 requires sunglasses for the female character.
These animal images would be handy for quickly learning a new person's name: you can meet a Kevin and imagine him next to the Kevin animal. In that way, the name is visually associated with this new person.
If a world fact rote learned for each cartoon animal then you can traverse the animal people in sequence and state 5 facts about over 100 countries. The first letters of a world fact such as Herat involves representing the H as a colour but the outfit is just there for variety: every 50 outfits, the same outfits occur again in the same sequence. An example is the white outfit of B0 because its fact is Benguela whcih begins with 'B'; the white outfit colour represents'B'; thent he eyes are the 'E' type because the second letter of Benguela is 'E'.
Since these are cartoon characters, they can have coloured outfits; I did want to encode information in each animal person outfit. Outfit colour fill can represent a letter or CH/SH (see the Colours article); outfit choice can represent a letter or CH/SH/TH (see the "Outfits 50" article). But the second letter of many words is either vowels or a small number of consonants; so that approach would have made some outfits occur far too often for there to be a distinct look to each cartoon animal person. I propose instead to use a small collection of eyes to overlay on the plain white eyes of the animals but only if the next letter of the spelling is one of these very common letters:
| Code | Name | Gender | Country | Item Type | Item Name | Outfit Colour (Fact Prefix) | Outfit (Loop 0 to 49) |
| A0 | Aaron | M | Afghanistan | City | Herat | 22 | 0 |
| A1 | Abraham | M | Afghanistan | City | Kandahar | 27 | 1 |
| A2 | Adam | M | Afghanistan | River | Amu Darya | 2 | 2 |
| A3 | Adrian | M | Afghanistan | River | Helmand River | 22 | 3 |
| A4 | Aiden | M | Afghanistan | Mountain | Noshaq | 15 | 4 |
| A5 | Alan | M | Algeria | City | Constantine | 17 | 5 |
| A6 | Alex | M | Algeria | City | Oran | 0 | 6 |
| A7 | Alfie | M | Algeria | River | Chelif River | 21 | 7 |
| A8 | Andrew | M | Algeria | River | Soummam River | 16 | 8 |
| A9 | Anthony | M | Algeria | Mountain | Mount Tahat | 24 | 9 |
| B0 | Barry | M | Angola | City | Benguela | 10 | 10 |
| B1 | Ben | M | Angola | City | Huambo | 22 | 11 |
| B2 | Bill | M | Angola | River | Congo River | 17 | 12 |
| B3 | Brendon | M | Angola | River | Cuanza River | 17 | 13 |
| B4 | Bob | M | Angola | Mountain | Mount Moco | 24 | 14 |
| B5 | Bradley | M | Argentina | City | Córdoba | 17 | 15 |
| B6 | Brandon | M | Argentina | City | Rosario | 23 | 16 |
| B7 | Brett | M | Argentina | River | Paraná River | 25 | 17 |
| B8 | Brian | M | Argentina | River | Uruguay River | 4 | 18 |
| B9 | Burt | M | Argentina | Mountain | Aconcagua | 2 | 19 |
| C0 | Carlos | M | Australia | City | Melbourne | 24 | 20 |
| C1 | Charles | M | Australia | City | Sydney | 16 | 21 |
| C2 | Chase | M | Australia | River | Darling River | 14 | 22 |
| C3 | Christian | M | Australia | River | Murray River | 24 | 23 |
| C4 | Christopher | M | Australia | Mountain | Mount Kosciuszko | 24 | 24 |
| C5 | Colin | M | Bangladesh | City | Chittagong | 21 | 25 |
| C6 | Connor | M | Bangladesh | City | Khulna | 27 | 26 |
| C7 | Craig | M | Bangladesh | River | Jamuna River | 11 | 27 |
| C8 | Curtis | M | Bangladesh | River | Padma River | 25 | 28 |
| C9 | Cedric | M | Bangladesh | Mountain | Saka Haphong | 16 | 29 |
| D0 | Damien | M | Belarus | City | Brest | 10 | 30 |
| D1 | Daniel | M | Belarus | City | Gomel | 13 | 31 |
| D2 | David | M | Belarus | River | Dnieper River | 14 | 32 |
| D3 | Dean | M | Belarus | River | Neman River | 15 | 33 |
| D4 | Declan | M | Belarus | Mountain | Dzyarzhynskaya Hara | 14 | 34 |
| D5 | Derek | M | Benin | City | Cotonou | 17 | 35 |
| D6 | Dominic | M | Benin | City | Parakou | 25 | 36 |
| D7 | Dylan | M | Benin | River | Niger River | 15 | 37 |
| D8 | Donald | M | Benin | River | Ouémé River | 0 | 38 |
| D9 | Dennis | M | Benin | Mountain | Mont Sokbaro | 24 | 39 |
| E0 | Edward | M | Bolivia | City | El Alto | 3 | 40 |
| E1 | Eamon | M | Bolivia | City | Santa Cruz de la Sierra | 16 | 41 |
| E2 | Elijah | M | Bolivia | River | Beni River | 10 | 42 |
| E3 | Elliott | M | Bolivia | River | Mamoré River | 24 | 43 |
| E4 | Emilio | M | Bolivia | Mountain | Sajama | 16 | 44 |
| E5 | Emmanuel | M | Botswana | City | Francistown | 19 | 45 |
| E6 | Eric | M | Botswana | City | Maun | 24 | 46 |
| E7 | Ethan | M | Botswana | River | Limpopo River | 20 | 47 |
| E8 | Ezra | M | Botswana | River | Okavango River | 0 | 48 |
| E9 | Ezekiel | M | Botswana | Mountain | Otse Hill | 0 | 49 |
| F0 | Felix | M | Brazil | City | Rio de Janeiro | 23 | 0 |
| F1 | Finn | M | Brazil | City | São Paulo | 16 | 1 |
| F2 | Francis | M | Brazil | River | Amazon River | 2 | 2 |
| F3 | Frank | M | Brazil | River | São Francisco River | 16 | 3 |
| F4 | Fred | M | Brazil | Mountain | Pico da Neblina | 25 | 4 |
| F5 | Fergus | M | Bulgaria | City | Plovdiv | 25 | 5 |
| F6 | Fred | M | Bulgaria | City | Varna | 9 | 6 |
| F7 | Filippe | M | Bulgaria | River | Danube River | 14 | 7 |
| F8 | Fernando | M | Bulgaria | River | Maritsa River | 24 | 8 |
| F9 | Forrest | M | Bulgaria | Mountain | Musala | 24 | 9 |
| G0 | Gabriel | M | Burkina Faso | City | Bobo-Dioulasso | 10 | 10 |
| G1 | George | M | Burkina Faso | City | Koudougou | 27 | 11 |
| G2 | Gavin | M | Burkina Faso | River | Black Volta | 10 | 12 |
| G3 | Greg | M | Burkina Faso | River | White Volta | 5 | 13 |
| G4 | Gary | M | Burkina Faso | Mountain | Tena Kourou | 18 | 14 |
| G5 | Gerald | M | Cambodia | City | Battambang | 10 | 15 |
| G6 | Gino | M | Cambodia | City | Siem Reap | 16 | 16 |
| G7 | Glenn | M | Cambodia | River | Mekong River | 24 | 17 |
| G8 | Guy | M | Cambodia | River | Tonlé Sap River | 18 | 18 |
| G9 | Giuseppe | M | Cambodia | Mountain | Phnom Aural | 25 | 19 |
| H0 | Harry | M | Cameroon | City | Douala | 14 | 20 |
| H1 | Henry | M | Cameroon | City | Garoua | 13 | 21 |
| H2 | Harrison | M | Cameroon | River | Benue River | 10 | 22 |
| H3 | Hugo | M | Cameroon | River | Sanaga River | 16 | 23 |
| H4 | Harold | M | Cameroon | Mountain | Mount Cameroon | 24 | 24 |
| H5 | Hans | M | Canada | City | Montreal | 24 | 25 |
| H6 | Hector | M | Canada | City | Toronto | 18 | 26 |
| H7 | Howard | M | Canada | River | Mackenzie River | 24 | 27 |
| H8 | Herman | M | Canada | River | St. Lawrence River | 16 | 28 |
| H9 | Hugh | M | Canada | Mountain | Mount Logan | 24 | 29 |
| I0 | Isaac | M | Central African Republic | City | Berberati | 10 | 30 |
| I1 | Isaiah | M | Central African Republic | City | Bimbo | 10 | 31 |
| I2 | Ian | M | Central African Republic | River | Sangha River | 16 | 32 |
| I3 | Ivan | M | Central African Republic | River | Ubangi River | 4 | 33 |
| I4 | Ira | M | Central African Republic | Mountain | Mont Ngaoui | 24 | 34 |
| I5 | Imran | M | Chad | City | Moundou | 24 | 35 |
| I6 | Johan | M | Chad | City | Sarh | 16 | 36 |
| I7 | Jerome | M | Chad | River | Chari River | 21 | 37 |
| I8 | Jonas | M | Chad | River | Logone River | 20 | 38 |
| I9 | Julian | M | Chad | Mountain | Emi Koussi | 3 | 39 |
| J0 | Jack | M | Chile | City | Concepción | 17 | 40 |
| J1 | Joseph | M | Chile | City | Valparaíso | 9 | 41 |
| J2 | Jayden | M | Chile | River | Biobío River | 10 | 42 |
| J3 | John | M | Chile | River | Loa River | 20 | 43 |
| J4 | Jeremy | M | Chile | Mountain | Ojos del Salado | 0 | 44 |
| J5 | Jose | M | China | City | Guangzhou | 13 | 45 |
| J6 | Jason | M | China | City | Shanghai | 12 | 46 |
| J7 | Juan | M | China | River | Yangtze River | 8 | 47 |
| J8 | Jake | M | China | River | Yellow River | 8 | 48 |
| J9 | Jay | M | China | Mountain | Mount Everest | 24 | 49 |
| K0 | Kevin | M | Colombia | City | Cali | 17 | 0 |
| K1 | Kyle | M | Colombia | City | Medellín | 24 | 1 |
| K2 | Kieran | M | Colombia | River | Cauca River | 17 | 2 |
| K3 | Keith | M | Colombia | River | Magdalena River | 24 | 3 |
| K4 | Ken | M | Colombia | Mountain | Pico Cristóbal Colón | 25 | 4 |
| K5 | Lionel | M | Democratic Republic of the Congo | City | Kisangani | 27 | 5 |
| K6 | Leo | M | Democratic Republic of the Congo | City | Lubumbashi | 20 | 6 |
| K7 | Louis | M | Democratic Republic of the Congo | River | Congo River | 17 | 7 |
| K8 | Miguel | M | Democratic Republic of the Congo | River | Kasai River | 27 | 8 |
| K9 | Marcel | M | Democratic Republic of the Congo | Mountain | Mount Stanley | 24 | 9 |
| L0 | Lucas | M | Ecuador | City | Cuenca | 17 | 10 |
| L1 | Logan | M | Ecuador | City | Guayaquil | 13 | 11 |
| L2 | Luke | M | Ecuador | River | Guayas River | 13 | 12 |
| L3 | Leonard | M | Ecuador | River | Napo River | 15 | 13 |
| L4 | Luis | M | Ecuador | Mountain | Chimborazo | 21 | 14 |
| L5 | Lennox | M | Egypt | City | Alexandria | 2 | 15 |
| L6 | Lawrence | M | Egypt | City | Giza | 13 | 16 |
| L7 | Lance | M | Egypt | River | Bahr Yussef | 10 | 17 |
| L8 | Larry | M | Egypt | River | Nile River | 15 | 18 |
| L9 | Lloyd | M | Egypt | Mountain | Mount Catherine | 24 | 19 |
| M0 | Matthew | M | Eritrea | City | Keren | 27 | 20 |
| M1 | Mark | M | Eritrea | City | Massawa | 24 | 21 |
| M2 | Mike | M | Eritrea | River | Barka River | 10 | 22 |
| M3 | Max | M | Eritrea | River | Gash River | 13 | 23 |
| M4 | Miles | M | Eritrea | Mountain | Emba Soira | 3 | 24 |
| M5 | Marcus | M | Ethiopia | City | Dire Dawa | 14 | 25 |
| M6 | Malcolm | M | Ethiopia | City | Mekelle | 24 | 26 |
| M7 | Martin | M | Ethiopia | River | Awash River | 2 | 27 |
| M8 | Mohammed | M | Ethiopia | River | Blue Nile | 10 | 28 |
| M9 | Maurice | M | Ethiopia | Mountain | Ras Dashen | 23 | 29 |
| N0 | Nathan | M | Finland | City | Tampere | 18 | 30 |
| N1 | Nicholas | M | Finland | City | Turku | 18 | 31 |
| N2 | Neil | M | Finland | River | Kemijoki | 27 | 32 |
| N3 | Nassir | M | Finland | River | Oulujoki | 0 | 33 |
| N4 | Nino | M | Finland | Mountain | Halti | 22 | 34 |
| N5 | Norman | M | France | City | Lyon | 20 | 35 |
| N6 | Nelson | M | France | City | Marseille | 24 | 36 |
| N7 | Noah | M | France | River | Loire River | 20 | 37 |
| N8 | Noel | M | France | River | Seine River | 16 | 38 |
| N9 | Ned | M | France | Mountain | Mont Blanc | 24 | 39 |
| O0 | Oliver | M | Gabon | City | Franceville | 19 | 40 |
| O1 | Owen | M | Gabon | City | Port-Gentil | 25 | 41 |
| O2 | Omar | M | Gabon | River | Komo River | 27 | 42 |
| O3 | Oscar | M | Gabon | River | Ogooué River | 0 | 43 |
| O4 | Otis | M | Gabon | Mountain | Mont Iboundji | 24 | 44 |
| O5 | Ozzie | M | Germany | City | Hamburg | 22 | 45 |
| O6 | Amir | M | Germany | City | Munich | 24 | 46 |
| O7 | Hassan | M | Germany | River | Danube River | 14 | 47 |
| O8 | Rohan | M | Germany | River | Rhine River | 23 | 48 |
| O9 | Vihaan | M | Germany | Mountain | Zugspitze | 7 | 49 |
| P0 | Patrick | M | Ghana | City | Kumasi | 27 | 0 |
| P1 | Pedro | M | Ghana | City | Tamale | 18 | 1 |
| P2 | Peter | M | Ghana | River | Pra River | 25 | 2 |
| P3 | Philip | M | Ghana | River | Volta River | 9 | 3 |
| P4 | Pablo | M | Ghana | Mountain | Mount Afadja | 24 | 4 |
| P5 | Pierre | M | Greece | City | Patras | 25 | 5 |
| P6 | Paul | M | Greece | City | Thessaloniki | 18 | 6 |
| P7 | Pascal | M | Greece | River | Aliakmon River | 2 | 7 |
| P8 | Pearce | M | Greece | River | Evros River | 3 | 8 |
| P9 | Percy | M | Greece | Mountain | Mount Olympus | 24 | 9 |
| Q0 | Quentin | M | Guinea | City | Kankan | 27 | 10 |
| Q1 | Roger | M | Guinea | City | Nzérékoré | 15 | 11 |
| Q2 | Ross | M | Guinea | River | Gambia River | 13 | 12 |
| Q3 | Reuben | M | Guinea | River | Niger River | 15 | 13 |
| Q4 | Roy | M | Guinea | Mountain | Mount Nimba | 24 | 14 |
| Q5 | Raphael | M | Guyana | City | Linden | 20 | 15 |
| Q6 | Ronan | M | Guyana | City | New Amsterdam | 15 | 16 |
| Q7 | Ryan | M | Guyana | River | Demerara River | 14 | 17 |
| Q8 | Ron | M | Guyana | River | Essequibo River | 3 | 18 |
| Q9 | Rudy | M | Guyana | Mountain | Mount Roraima | 24 | 19 |
| R0 | Robert | M | Honduras | City | La Ceiba | 20 | 20 |
| R1 | Rory | M | Honduras | City | San Pedro Sula | 16 | 21 |
| R2 | Raymond | M | Honduras | River | Patuca River | 25 | 22 |
| R3 | Ricardo | M | Honduras | River | Ulúa River | 4 | 23 |
| R4 | Richard | M | Honduras | Mountain | Cerro Las Minas | 17 | 24 |
| R5 | Russell | M | India | City | Bangalore | 10 | 25 |
| R6 | Reed | M | India | City | Mumbai | 24 | 26 |
| R7 | Ronald | M | India | River | Brahmaputra River | 10 | 27 |
| R8 | Reece | M | India | River | Ganges River | 13 | 28 |
| R9 | Rio | M | India | Mountain | Kangchenjunga | 27 | 29 |
| S0 | Samuel | M | Indonesia | City | Bandung | 10 | 30 |
| S1 | Sebastian | M | Indonesia | City | Surabaya | 16 | 31 |
| S2 | Sergio | M | Indonesia | River | Kapuas River | 27 | 32 |
| S3 | Steven | M | Indonesia | River | Mahakam River | 24 | 33 |
| S4 | Sean | M | Indonesia | Mountain | Puncak Jaya | 25 | 34 |
| S5 | Scott | M | Iran | City | Isfahan | 1 | 35 |
| S6 | Samir | M | Iran | City | Mashhad | 24 | 36 |
| S7 | Salem | M | Iran | River | Aras River | 2 | 37 |
| S8 | Syed | M | Iran | River | Karun River | 27 | 38 |
| S9 | Simon | M | Iran | Mountain | Mount Damavand | 24 | 39 |
| T0 | Theo | M | Iraq | City | Basra | 10 | 40 |
| T1 | Troy | M | Iraq | City | Mosul | 24 | 41 |
| T2 | Thomas | M | Iraq | River | Euphrates River | 3 | 42 |
| T3 | Tony | M | Iraq | River | Tigris River | 18 | 43 |
| T4 | Terrance | M | Iraq | Mountain | Cheekha Dar | 21 | 44 |
| T5 | Toby | M | Italy | City | Milan | 24 | 45 |
| T6 | Tom | M | Italy | City | Naples | 15 | 46 |
| T7 | Trevor | M | Italy | River | Po River | 25 | 47 |
| T8 | Tim | M | Italy | River | Tiber River | 18 | 48 |
| T9 | Tristan | M | Italy | Mountain | Mont Blanc | 24 | 49 |
| U0 | Ulysses | M | Ivory Coast | City | Abidjan | 2 | 0 |
| U1 | Uri | M | Ivory Coast | City | Bouaké | 10 | 1 |
| U2 | Umberto | M | Ivory Coast | River | Bandama River | 10 | 2 |
| U3 | Santiago | M | Ivory Coast | River | Comoé River | 17 | 3 |
| U4 | Seth | M | Ivory Coast | Mountain | Mount Nimba | 24 | 4 |
| U5 | Spencer | M | Japan | City | Nagoya | 15 | 5 |
| U6 | Solomon | M | Japan | City | Osaka | 0 | 6 |
| U7 | Stanley | M | Japan | River | Shinano River | 12 | 7 |
| U8 | Stephan | M | Japan | River | Tone River | 18 | 8 |
| U9 | Tyson | M | Japan | Mountain | Mount Fuji | 24 | 9 |
| V0 | Vincent | M | Kazakhstan | City | Almaty | 2 | 10 |
| V1 | Vladimir | M | Kazakhstan | City | Shymkent | 12 | 11 |
| V2 | Vito | M | Kazakhstan | River | Irtysh River | 1 | 12 |
| V3 | Vidal | M | Kazakhstan | River | Ural River | 4 | 13 |
| V4 | Valerio | M | Kazakhstan | Mountain | Khan Tengri | 27 | 14 |
| V5 | Vaughn | M | Kenya | City | Kisumu | 27 | 15 |
| V6 | Vivek | M | Kenya | City | Mombasa | 24 | 16 |
| V7 | Vander | M | Kenya | River | Athi-Galana-Sabaki River | 2 | 17 |
| V8 | Vikram | M | Kenya | River | Tana River | 18 | 18 |
| V9 | Victor | M | Kenya | Mountain | Mount Kenya | 24 | 19 |
| W0 | William | M | Kyrgyzstan | City | Jalal-Abad | 11 | 20 |
| W1 | Wesley | M | Kyrgyzstan | City | Osh | 0 | 21 |
| W2 | Walter | M | Kyrgyzstan | River | Kara Darya | 27 | 22 |
| W3 | Wallace | M | Kyrgyzstan | River | Naryn River | 15 | 23 |
| W4 | Warren | M | Kyrgyzstan | Mountain | Jengish Chokusu | 11 | 24 |
| W5 | Winston | M | Laos | City | Luang Prabang | 20 | 25 |
| W6 | Wayne | M | Laos | City | Savannakhet | 16 | 26 |
| W7 | Wade | M | Laos | River | Mekong River | 24 | 27 |
| W8 | Willis | M | Laos | River | Nam Ou | 15 | 28 |
| W9 | Ishaan | M | Laos | Mountain | Phou Bia | 25 | 29 |
| X0 | Xavier | M | Liberia | City | Buchanan | 10 | 30 |
| X1 | Mustafa | M | Liberia | City | Gbarnga | 13 | 31 |
| X2 | Avyaan | M | Liberia | River | Cavalla River | 17 | 32 |
| X3 | Deepak | M | Liberia | River | St. Paul River | 16 | 33 |
| X4 | Ganesha | M | Liberia | Mountain | Mount Wuteve | 24 | 34 |
| X5 | Krishna | M | Libya | City | Benghazi | 10 | 35 |
| X6 | Manish | M | Libya | City | Misrata | 24 | 36 |
| X7 | Rahul | M | Libya | River | Wadi al Kuf | 5 | 37 |
| X8 | Ravindra | M | Libya | River | Wadi Baht | 5 | 38 |
| X9 | Siddhartha | M | Libya | Mountain | Bikku Bitti | 10 | 39 |
| Y0 | Yousef | M | Madagascar | City | Antsirabe | 2 | 40 |
| Y1 | Yan | M | Madagascar | City | Toamasina | 18 | 41 |
| Y2 | Sukhwinder | M | Madagascar | River | Betsiboka River | 10 | 42 |
| Y3 | Surendra | M | Madagascar | River | Tsiribihina River | 18 | 43 |
| Y4 | Vishnu | M | Madagascar | Mountain | Maromokotro | 24 | 44 |
| Y5 | Aravind | M | Malawi | City | Blantyre | 10 | 45 |
| Y6 | Ashwin | M | Malawi | City | Zomba | 7 | 46 |
| Y7 | Chandra | M | Malawi | River | Shire River | 12 | 47 |
| Y8 | Harsha | M | Malawi | River | Songwe River | 16 | 48 |
| Y9 | Jitendra | M | Malawi | Mountain | Mount Mulanje | 24 | 49 |
| Z0 | Zahir | M | Malaysia | City | George Town | 13 | 0 |
| Z1 | Kamal | M | Malaysia | City | Johor Bahru | 11 | 1 |
| Z2 | Mahendra | M | Malaysia | River | Pahang River | 25 | 2 |
| Z3 | Mohandas | M | Malaysia | River | Rajang River | 23 | 3 |
| Z4 | Rakesh | M | Malaysia | Mountain | Mount Kinabalu | 24 | 4 |
| Z5 | Suraj | M | Mali | City | Sikasso | 16 | 5 |
| Z6 | Anant | M | Mali | City | Timbuktu | 18 | 6 |
| Z7 | Bhaskar | M | Mali | River | Niger River | 15 | 7 |
| Z8 | Dilip | M | Mali | River | Senegal River | 16 | 8 |
| Z9 | Dinesh | M | Mali | Mountain | Hombori Tondo | 22 | 9 |
| 0A | Audrey | F | Mauritania | City | Kiffa | 27 | 10 |
| 1A | Alice | F | Mauritania | City | Nouadhibou | 15 | 11 |
| 2A | Anna | F | Mauritania | River | Karakoro River | 27 | 12 |
| 3A | Andrea | F | Mauritania | River | Senegal River | 16 | 13 |
| 4A | Amy | F | Mauritania | Mountain | Kediet ej Jill | 27 | 14 |
| 5A | Anabelle | F | Mexico | City | Guadalajara | 13 | 15 |
| 6A | Adriana | F | Mexico | City | Monterrey | 24 | 16 |
| 7A | Alexis | F | Mexico | River | Lerma River | 20 | 17 |
| 8A | Amanda | F | Mexico | River | Rio Grande | 23 | 18 |
| 9A | Amber | F | Mexico | Mountain | Pico de Orizaba | 25 | 19 |
| 0B | Bella | F | Mongolia | City | Darkhan | 14 | 20 |
| 1B | Bridget | F | Mongolia | City | Erdenet | 3 | 21 |
| 2B | Brenda | F | Mongolia | River | Orkhon River | 0 | 22 |
| 3B | Beverly | F | Mongolia | River | Selenge River | 16 | 23 |
| 4B | Brie | F | Mongolia | Mountain | Khüiten Peak | 27 | 24 |
| 5B | Belinda | F | Morocco | City | Casablanca | 17 | 25 |
| 6B | Bernadette | F | Morocco | City | Marrakesh | 24 | 26 |
| 7B | Brittany | F | Morocco | River | Moulouya River | 24 | 27 |
| 8B | Beth | F | Morocco | River | Oum Er-Rbia | 0 | 28 |
| 9B | Bianca | F | Morocco | Mountain | Jebel Toubkal | 11 | 29 |
| 0C | Charlotte | F | Mozambique | City | Beira | 10 | 30 |
| 1C | Camilla | F | Mozambique | City | Nampula | 15 | 31 |
| 2C | Chloe | F | Mozambique | River | Limpopo River | 20 | 32 |
| 3C | Claire | F | Mozambique | River | Zambezi River | 7 | 33 |
| 4C | Carmen | F | Mozambique | Mountain | Mount Binga | 24 | 34 |
| 5C | Christina | F | Myanmar | City | Mandalay | 24 | 35 |
| 6C | Carolyn | F | Myanmar | City | Yangon | 8 | 36 |
| 7C | Celine | F | Myanmar | River | Irrawaddy River | 1 | 37 |
| 8C | Cindy | F | Myanmar | River | Salween River | 16 | 38 |
| 9C | Catherine | F | Myanmar | Mountain | Hkakabo Razi | 22 | 39 |
| 0D | Danielle | F | Namibia | City | Swakopmund | 16 | 40 |
| 1D | Daisy | F | Namibia | City | Walvis Bay | 5 | 41 |
| 2D | Delia | F | Namibia | River | Okavango River | 0 | 42 |
| 3D | Demi | F | Namibia | River | Orange River | 0 | 43 |
| 4D | Diana | F | Namibia | Mountain | Brandberg Mountain | 10 | 44 |
| 5D | Daphne | F | Nepal | City | Biratnagar | 10 | 45 |
| 6D | Drew | F | Nepal | City | Pokhara | 25 | 46 |
| 7D | Dawn | F | Nepal | River | Gandaki River | 13 | 47 |
| 8D | Dorothy | F | Nepal | River | Koshi River | 27 | 48 |
| 9D | Doris | F | Nepal | Mountain | Mount Everest | 24 | 49 |
| 0E | Emma | F | New Zealand | City | Auckland | 2 | 0 |
| 1E | Elizabeth | F | New Zealand | City | Christchurch | 21 | 1 |
| 2E | Eleanor | F | New Zealand | River | Clutha River | 17 | 2 |
| 3E | Emily | F | New Zealand | River | Waikato River | 5 | 3 |
| 4E | Ella | F | New Zealand | Mountain | Aoraki / Mount Cook | 2 | 4 |
| 5E | Esther | F | Nicaragua | City | Granada | 13 | 5 |
| 6E | Elaine | F | Nicaragua | City | León | 20 | 6 |
| 7E | Eve | F | Nicaragua | River | Coco River | 17 | 7 |
| 8E | Erika | F | Nicaragua | River | San Juan River | 16 | 8 |
| 9E | Evelyn | F | Nicaragua | Mountain | Mogotón | 24 | 9 |
| 0F | Faith | F | Niger | City | Maradi | 24 | 10 |
| 1F | Fatima | F | Niger | City | Zinder | 7 | 11 |
| 2F | Felicity | F | Niger | River | Komadougou Yobe | 27 | 12 |
| 3F | Fiona | F | Niger | River | Niger River | 15 | 13 |
| 4F | Francesca | F | Niger | Mountain | Mont Idoukal-n-Taghès | 24 | 14 |
| 5F | Frida | F | Nigeria | City | Kano | 27 | 15 |
| 6F | Fay | F | Nigeria | City | Lagos | 20 | 16 |
| 7F | Fern | F | Nigeria | River | Benue River | 10 | 17 |
| 8F | Flavia | F | Nigeria | River | Niger River | 15 | 18 |
| 9F | Fernanda | F | Nigeria | Mountain | Chappal Waddi | 21 | 19 |
| 0G | Grace | F | North Korea | City | Chongjin | 21 | 20 |
| 1G | Georgina | F | North Korea | City | Hamhung | 22 | 21 |
| 2G | Gabriella | F | North Korea | River | Tumen River | 18 | 22 |
| 3G | Gloria | F | North Korea | River | Yalu River | 8 | 23 |
| 4G | Geraldine | F | North Korea | Mountain | Paektu Mountain | 25 | 24 |
| 5G | Gina | F | Norway | City | Bergen | 10 | 25 |
| 6G | Gwen | F | Norway | City | Trondheim | 18 | 26 |
| 7G | Greta | F | Norway | River | Glomma | 13 | 27 |
| 8G | Gemma | F | Norway | River | Tana River | 18 | 28 |
| 9G | Giselle | F | Norway | Mountain | Galdhøpiggen | 13 | 29 |
| 0H | Hazel | F | Oman | City | Salalah | 16 | 30 |
| 1H | Hailey | F | Oman | City | Sohar | 16 | 31 |
| 2H | Helen | F | Oman | River | Wadi Bani Khalid | 5 | 32 |
| 3H | Heidi | F | Oman | River | Wadi Darbat | 5 | 33 |
| 4H | Hannah | F | Oman | Mountain | Jabal Shams | 11 | 34 |
| 5H | Holly | F | Pakistan | City | Karachi | 27 | 35 |
| 6H | Heather | F | Pakistan | City | Lahore | 20 | 36 |
| 7H | Harmonie | F | Pakistan | River | Indus River | 1 | 37 |
| 8H | Hillary | F | Pakistan | River | Jhelum River | 11 | 38 |
| 9H | Harriet | F | Pakistan | Mountain | K2 | 27 | 39 |
| 0I | Isabelle | F | Papua New Guinea | City | Lae | 20 | 40 |
| 1I | Ivy | F | Papua New Guinea | City | Mount Hagen | 24 | 41 |
| 2I | Irene | F | Papua New Guinea | River | Fly River | 19 | 42 |
| 3I | Ivanna | F | Papua New Guinea | River | Sepik River | 16 | 43 |
| 4I | Iliana | F | Papua New Guinea | Mountain | Mount Wilhelm | 24 | 44 |
| 5I | Ida | F | Paraguay | City | Ciudad del Este | 17 | 45 |
| 6I | Imogen | F | Paraguay | City | Encarnación | 3 | 46 |
| 7I | Jordan | F | Paraguay | River | Paraguay River | 25 | 47 |
| 8I | Jennifer | F | Paraguay | River | Paraná River | 25 | 48 |
| 9I | Jessica | F | Paraguay | Mountain | Cerro Peró | 17 | 49 |
| 0J | Jade | F | Peru | City | Arequipa | 2 | 0 |
| 1J | Jennifer | F | Peru | City | Cusco | 17 | 1 |
| 2J | Janet | F | Peru | River | Amazon River | 2 | 2 |
| 3J | Jane | F | Peru | River | Ucayali River | 4 | 3 |
| 4J | Jacqueline | F | Peru | Mountain | Huascarán | 22 | 4 |
| 5J | June | F | Philippines | City | Cebu City | 17 | 5 |
| 6J | Julia | F | Philippines | City | Davao City | 14 | 6 |
| 7J | Juliette | F | Philippines | River | Cagayan River | 17 | 7 |
| 8J | Julianna | F | Philippines | River | Rio Grande de Mindanao | 23 | 8 |
| 9J | Joy | F | Philippines | Mountain | Mount Apo | 24 | 9 |
| 0K | Kim | F | Poland | City | Kraków | 27 | 10 |
| 1K | Kelly | F | Poland | City | Łódź | 20 | 11 |
| 2K | Kathleen | F | Poland | River | Oder River | 0 | 12 |
| 3K | Keira | F | Poland | River | Vistula River | 9 | 13 |
| 4K | Kate | F | Poland | Mountain | Rysy | 23 | 14 |
| 5K | Karina | F | Portugal | City | Braga | 10 | 15 |
| 6K | Kelly | F | Portugal | City | Porto | 25 | 16 |
| 7K | Judith | F | Portugal | River | Douro River | 14 | 17 |
| 8K | Jasmine | F | Portugal | River | Tagus River | 18 | 18 |
| 9K | Joan | F | Portugal | Mountain | Mount Pico | 24 | 19 |
| 0L | Layla | F | Republic of the Congo | City | Dolisie | 14 | 20 |
| 1L | Leah | F | Republic of the Congo | City | Pointe-Noire | 25 | 21 |
| 2L | Lily | F | Republic of the Congo | River | Congo River | 17 | 22 |
| 3L | Lucy | F | Republic of the Congo | River | Kouilou-Niari River | 27 | 23 |
| 4L | Lydia | F | Republic of the Congo | Mountain | Mount Nabeba | 24 | 24 |
| 5L | Lauren | F | Romania | City | Cluj-Napoca | 17 | 25 |
| 6L | Louise | F | Romania | City | Timișoara | 18 | 26 |
| 7L | Liv | F | Romania | River | Danube River | 14 | 27 |
| 8L | Linda | F | Romania | River | Mureș River | 24 | 28 |
| 9L | Leanne | F | Romania | Mountain | Moldoveanu Peak | 24 | 29 |
| 0M | Mia | F | Russia | City | Novosibirsk | 15 | 30 |
| 1M | Madeleine | F | Russia | City | Saint Petersburg | 16 | 31 |
| 2M | Maria | F | Russia | River | Lena River | 20 | 32 |
| 3M | Margaret | F | Russia | River | Volga River | 9 | 33 |
| 4M | Melanie | F | Russia | Mountain | Mount Elbrus | 24 | 34 |
| 5M | Mary | F | Saudi Arabia | City | Jeddah | 11 | 35 |
| 6M | Melissa | F | Saudi Arabia | City | Mecca | 24 | 36 |
| 7M | Michelle | F | Saudi Arabia | River | Wadi Al-Dawasir | 5 | 37 |
| 8M | Marie | F | Saudi Arabia | River | Wadi Bishah | 5 | 38 |
| 9M | Monica | F | Saudi Arabia | Mountain | Jabal Sawda | 11 | 39 |
| 0N | Naomi | F | Senegal | City | Saint-Louis | 16 | 40 |
| 1N | Natalie | F | Senegal | City | Thiès | 18 | 41 |
| 2N | Nina | F | Senegal | River | Gambia River | 13 | 42 |
| 3N | Nicole | F | Senegal | River | Senegal River | 16 | 43 |
| 4N | Nadia | F | Senegal | Mountain | Nepen Diakha | 15 | 44 |
| 5N | Natasha | F | Somalia | City | Bosaso | 10 | 45 |
| 6N | Norah | F | Somalia | City | Hargeisa | 22 | 46 |
| 7N | Nancy | F | Somalia | River | Jubba River | 11 | 47 |
| 8N | Nola | F | Somalia | River | Shabelle River | 12 | 48 |
| 9N | Neve | F | Somalia | Mountain | Shimbiris | 12 | 49 |
| 0O | Olivia | F | South Africa | City | Cape Town | 17 | 0 |
| 1O | Olga | F | South Africa | City | Johannesburg | 11 | 1 |
| 2O | Jenny | F | South Africa | River | Limpopo River | 20 | 2 |
| 3O | Jude | F | South Africa | River | Orange River | 0 | 3 |
| 4O | Lisa | F | South Africa | Mountain | Mafadi | 24 | 4 |
| 5O | Lindsay | F | South Sudan | City | Malakal | 24 | 5 |
| 6O | Lorraine | F | South Sudan | City | Wau | 5 | 6 |
| 7O | Marilyn | F | South Sudan | River | Sobat River | 16 | 7 |
| 8O | Martha | F | South Sudan | River | White Nile | 5 | 8 |
| 9O | Meghan | F | South Sudan | Mountain | Kinyeti | 27 | 9 |
| 0P | Polly | F | Spain | City | Barcelona | 10 | 10 |
| 1P | Phoebe | F | Spain | City | Valencia | 9 | 11 |
| 2P | Paige | F | Spain | River | Ebro River | 3 | 12 |
| 3P | Penny | F | Spain | River | Tagus River | 18 | 13 |
| 4P | Priscilla | F | Spain | Mountain | Teide | 18 | 14 |
| 5P | Patricia | F | Sudan | City | Omdurman | 0 | 15 |
| 6P | Pippa | F | Sudan | City | Port Sudan | 25 | 16 |
| 7P | Pamela | F | Sudan | River | Blue Nile | 10 | 17 |
| 8P | Philippa | F | Sudan | River | Nile River | 15 | 18 |
| 9P | Paula | F | Sudan | Mountain | Jebel Marra | 11 | 19 |
| 0Q | Robyn | F | Suriname | City | Lelydorp | 20 | 20 |
| 1Q | Serena | F | Suriname | City | Nieuw Nickerie | 15 | 21 |
| 2Q | Sabrina | F | Suriname | River | Marowijne River | 24 | 22 |
| 3Q | Skye | F | Suriname | River | Suriname River | 16 | 23 |
| 4Q | Stephanie | F | Suriname | Mountain | Juliana Top | 11 | 24 |
| 5Q | Simone | F | Sweden | City | Gothenburg | 13 | 25 |
| 6Q | Salma | F | Sweden | City | Malmö | 24 | 26 |
| 7Q | Susan | F | Sweden | River | Göta älv | 13 | 27 |
| 8Q | Sonia | F | Sweden | River | Torne River | 18 | 28 |
| 9Q | Silvia | F | Sweden | Mountain | Kebnekaise | 27 | 29 |
| 0R | Ruby | F | Syria | City | Aleppo | 2 | 30 |
| 1R | Rose | F | Syria | City | Homs | 22 | 31 |
| 2R | Reese | F | Syria | River | Euphrates River | 3 | 32 |
| 3R | Ruth | F | Syria | River | Orontes River | 0 | 33 |
| 4R | Rachel | F | Syria | Mountain | Mount Hermon | 24 | 34 |
| 5R | Rebecca | F | Tajikistan | City | Khujand | 27 | 35 |
| 6R | Rosemary | F | Tajikistan | City | Kulob | 27 | 36 |
| 7R | Ramona | F | Tajikistan | River | Panj River | 25 | 37 |
| 8R | Raquel | F | Tajikistan | River | Vakhsh River | 9 | 38 |
| 9R | Rosalind | F | Tajikistan | Mountain | Ismoil Somoni Peak | 1 | 39 |
| 0S | Sophie | F | Tanzania | City | Dar es Salaam | 14 | 40 |
| 1S | Scarlett | F | Tanzania | City | Mwanza | 24 | 41 |
| 2S | Stella | F | Tanzania | River | Rufiji River | 23 | 42 |
| 3S | Sadie | F | Tanzania | River | Ruvuma River | 23 | 43 |
| 4S | Sarah | F | Tanzania | Mountain | Mount Kilimanjaro | 24 | 44 |
| 5S | Samantha | F | Thailand | City | Chiang Mai | 21 | 45 |
| 6S | Summer | F | Thailand | City | Phuket | 25 | 46 |
| 7S | Sara | F | Thailand | River | Chao Phraya River | 21 | 47 |
| 8S | Selena | F | Thailand | River | Mekong River | 24 | 48 |
| 9T | Sydney | F | Thailand | Mountain | Doi Inthanon | 14 | 49 |
| 0T | Taylor | F | Tunisia | City | Sfax | 16 | 0 |
| 1T | Tessa | F | Tunisia | City | Sousse | 16 | 1 |
| 2T | Talia | F | Tunisia | River | Medjerda River | 24 | 2 |
| 3T | Tatum | F | Tunisia | River | Oued Miliane | 0 | 3 |
| 4T | Teresa | F | Tunisia | Mountain | Jebel ech Chambi | 11 | 4 |
| 5T | Tatiana | F | Turkey | City | Istanbul | 1 | 5 |
| 6T | Tilly | F | Turkey | City | Izmir | 1 | 6 |
| 7T | Tara | F | Turkey | River | Euphrates River | 3 | 7 |
| 8T | Tina | F | Turkey | River | Kızılırmak River | 27 | 8 |
| 9T | Tracy | F | Turkey | Mountain | Mount Ararat | 24 | 9 |
| 0U | Una | F | Turkmenistan | City | Mary | 24 | 10 |
| 1U | Ursula | F | Turkmenistan | City | Türkmenabat | 18 | 11 |
| 2U | Stacy | F | Turkmenistan | River | Amu Darya | 2 | 12 |
| 3U | Aisha | F | Turkmenistan | River | Murgab River | 24 | 13 |
| 4U | Anika | F | Turkmenistan | Mountain | Aýrybaba | 2 | 14 |
| 5U | Arya | F | Uganda | City | Gulu | 13 | 15 |
| 6U | Ila | F | Uganda | City | Jinja | 11 | 16 |
| 7U | Laila | F | Uganda | River | Albert Nile | 2 | 17 |
| 8U | Maryam | F | Uganda | River | Victoria Nile | 9 | 18 |
| 9U | Maya | F | Uganda | Mountain | Mount Stanley | 24 | 19 |
| 0V | Violet | F | Ukraine | City | Kharkiv | 27 | 20 |
| 1V | Victoria | F | Ukraine | City | Odesa | 0 | 21 |
| 2V | Vivienne | F | Ukraine | River | Dnieper River | 14 | 22 |
| 3V | Valerie | F | Ukraine | River | Dniester River | 14 | 23 |
| 4V | Vanessa | F | Ukraine | Mountain | Hoverla | 22 | 24 |
| 5V | Veronica | F | United Kingdom | City | Birmingham | 10 | 25 |
| 6V | Virginia | F | United Kingdom | City | Manchester | 24 | 26 |
| 7V | Verna | F | United Kingdom | River | Severn River | 16 | 27 |
| 8V | Verona | F | United Kingdom | River | Thames River | 18 | 28 |
| 9V | Viola | F | United Kingdom | Mountain | Ben Nevis | 10 | 29 |
| 0W | Whitney | F | United States | City | Los Angeles | 20 | 30 |
| 1W | Winona | F | United States | City | New York City | 15 | 31 |
| 2W | Wanda | F | United States | River | Mississippi River | 24 | 32 |
| 3W | Arushi | F | United States | River | Missouri River | 24 | 33 |
| 4W | Pushpa | F | United States | Mountain | Denali | 14 | 34 |
| 5W | Samira | F | Uruguay | City | Paysandú | 25 | 35 |
| 6W | Veda | F | Uruguay | City | Salto | 16 | 36 |
| 7W | Ezhil | F | Uruguay | River | Río Negro | 23 | 37 |
| 8W | Indira | F | Uruguay | River | Uruguay River | 4 | 38 |
| 9W | Devika | F | Uruguay | Mountain | Cerro Catedral | 17 | 39 |
| 0X | Xena | F | Uzbekistan | City | Bukhara | 10 | 40 |
| 1X | Drishti | F | Uzbekistan | City | Samarkand | 16 | 41 |
| 2X | Esha | F | Uzbekistan | River | Amu Darya | 2 | 42 |
| 3X | Kalyani | F | Uzbekistan | River | Syr Darya | 16 | 43 |
| 4X | Karishme | F | Uzbekistan | Mountain | Khazret Sultan | 27 | 44 |
| 5X | Kaur | F | Venezuela | City | Maracaibo | 24 | 45 |
| 6X | Roshni | F | Venezuela | City | Valencia | 9 | 46 |
| 7X | Reshmi | F | Venezuela | River | Caroní River | 17 | 47 |
| 8X | Rupinder | F | Venezuela | River | Orinoco River | 0 | 48 |
| 9X | Saira | F | Venezuela | Mountain | Pico Bolívar | 25 | 49 |
| 0Y | Radha | F | Vietnam | City | Da Nang | 14 | 0 |
| 1Y | Aarna | F | Vietnam | City | Ho Chi Minh City | 22 | 1 |
| 2Y | Ahana | F | Vietnam | River | Mekong River | 24 | 2 |
| 3Y | Disha | F | Vietnam | River | Red River | 23 | 3 |
| 4Y | Kashvi | F | Vietnam | Mountain | Fansipan | 19 | 4 |
| 5Y | Kaven | F | Yemen | City | Aden | 2 | 5 |
| 6Y | Inaya | F | Yemen | City | Taiz | 18 | 6 |
| 7Y | Lasya | F | Yemen | River | Wadi Hadhramaut | 5 | 7 |
| 8Y | Sarika | F | Yemen | River | Wadi Mawr | 5 | 8 |
| 9Y | Yulia | F | Yemen | Mountain | Jabal An-Nabi Shu'ayb | 11 | 9 |
| 0Z | Zoe | F | Zambia | City | Kitwe | 27 | 10 |
| 1Z | Zara | F | Zambia | City | Ndola | 15 | 11 |
| 2Z | Nakshatra | F | Zambia | River | Kafue River | 27 | 12 |
| 3Z | Priya | F | Zambia | River | Zambezi River | 7 | 13 |
| 4Z | Adhira | F | Zambia | Mountain | Mafinga Central | 24 | 14 |
| 5Z | Charvi | F | Zimbabwe | City | Bulawayo | 10 | 15 |
| 6Z | Diva | F | Zimbabwe | City | Mutare | 24 | 16 |
| 7Z | Eshana | F | Zimbabwe | River | Limpopo River | 20 | 17 |
| 8Z | Jiya | F | Zimbabwe | River | Zambezi River | 7 | 18 |
| 9Z | Shakuntala | F | Zimbabwe | Mountain | Mount Nyangani | 24 | 19 |
The 520 animal people: 520 animal-based characters plus CH, SH, TH and ZH other combinations
Note: The system was originally for A to Z but then I wanted things like SH3, ZH4, TH5, 7CH; because I treat CH, SH, TH and ZH as if they are standalone letters; so I introduced some animation style people to this list - with a sci-fi theme to their outfits; plus 40 Shakespeare characters. So the total is 520 + 40 + 40 = 600 characters.
Letter-First Pairs
- O: O0 O1 O2 O3 O4 O5 O6 O7 O8 O9
- I: I0 I1 I2 I3 I4 I5 I6 I7 I8 I9
- A: A0 A1 A2 A3 A4 A5 A6 A7 A8 A9
- E: E0 E1 E2 E3 E4 E5 E6 E7 E8 E9
- U: U0 U1 U2 U3 U4 U5 U6 U7 U8 U9
- W: W0 W1 W2 W3 W4 W5 W6 W7 W8 W9
- X: X0 X1 X2 X3 X4 X5 X6 X7 X8 X9
- Z: Z0 Z1 Z2 Z3 Z4 Z5 Z6 Z7 Z8 Z9
- Y: Y0 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9
- V: V0 V1 V2 V3 V4 V5 V6 V7 V8 V9
- B: B0 B1 B2 B3 B4 B5 B6 B7 B8 B9
- J: J0 J1 J2 J3 J4 J5 J6 J7 J8 J9
- SH: SH0 SH1 SH2 SH3 SH4 SH5 SH6 SH7 SH8 SH9
- G: G0 G1 G2 G3 G4 G5 G6 G7 G8 G9
- D: D0 D1 D2 D3 D4 D5 D6 D7 D8 D9
- N: N0 N1 N2 N3 N4 N5 N6 N7 N8 N9
- S: S0 S1 S2 S3 S4 S5 S6 S7 S8 S9
- C: C0 C1 C2 C3 C4 C5 C6 C7 C8 C9
- T: T0 T1 T2 T3 T4 T5 T6 T7 T8 T9
- F: F0 F1 F2 F3 F4 F5 F6 F7 F8 F9
- L: L0 L1 L2 L3 L4 L5 L6 L7 L8 L9
- CH: CH0 CH1 CH2 CH3 CH4 CH5 CH6 CH7 CH8 CH9
- H: H0 H1 H2 H3 H4 H5 H6 H7 H8 H9
- R: R0 R1 R2 R3 R4 R5 R6 R7 R8 R9
- M: M0 M1 M2 M3 M4 M5 M6 M7 M8 M9
- P: P0 P1 P2 P3 P4 P5 P6 P7 P8 P9
- Q: Q0 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9
- K: K0 K1 K2 K3 K4 K5 K6 K7 K8 K9
- TH: TH0 TH1 TH2 TH3 TH4 TH5 TH6 TH7 TH8 TH9
- ZH: ZH0 ZH1 ZH2 ZH3 ZH4 ZH5 ZH6 ZH7 ZH8 ZH9
Digit-First Pairs
This collection of animal people represent a digit followed by a letter: