# data[].attributes.body
1. Red
2. Blue
3. Green
4. Pink
5. Yellow

# data[].attributes.body
1. Red.
2. Blue.
3. Brown.
4. White.
5. Yellow.

# data[].attributes.body
-Black
-Red
-Blue
-Purplue
-Grey

# data[].attributes.body
1.Black
2.white
3. Pink
4. yellow
5. blue

# data[].attributes.body
1.Behind
2. Between
3. Next to
4. On
5. In

# data[].attributes.body
1.- In front of
2.- On
3.- In
4.- Between
5.- Under

# data[].attributes.body
Orange
Pink
Yellow
Brown
Black

# data[].attributes.body
Red
blue
yellow
green
White

# data[].attributes.body
1.- Dentist
2.- Doctor
3.- Policeman
4.- Teacher
5.- Chef

# data[].attributes.body
-on
-in
-under
-next to
-over

# data[].attributes.body
Chef
Police Officer
Farmer

# data[].attributes.body
1. Nurse
2. Doctor
3. Chef

# data[].attributes.body
1. red
2. pink
3. blue
4. white
5. black

# data[].attributes.body
1. In front of.
2. Under.
3. On.
4. Between.
5. Next to.

# data[].attributes.body
1. on
2. in
3. under
4. between
5. over

# data[].attributes.body
Australia - Australian
Peru -  Peruvian
USA -  American
Spain - Spanish

# data[].attributes.body
under
in
in front of
between
next to

# data[].attributes.body
1. black
2. white
3. red
4. purple
5. blue

# data[].attributes.body
1. Doctor.
2. Nurse.
3. Teacher.

# data[].attributes.body
Red
yellow
blues
Orange
black

# data[].attributes.body
doctor
attorney
police

# data[].attributes.body
-Teacher
-Policeman
-Doctor
-Actor
-Chef

# data[].attributes.body
1. Between
2. Under
3. Around
4. On
5.In

# data[].attributes.body
1. ARGENTINA -  Argentine
2. MEXICO- Mexican
3. PERÚ- Peruvian

# data[].attributes.body
on
next to
Under
between
behind

# data[].attributes.body
Ruler
Blackboard
Desk
Bag
Books
Folders

# data[].attributes.body
1.- Chinese- China
2.- Peruvian- Peru
3.- British-Uk
4.- Russian- Russia
5.- Argentinian- Argentina

# data[].attributes.body
1. engineer
2. nurse
3. policeman

# data[].attributes.body
1. between
2. in
3. on
4. in front of
5. under

# data[].attributes.body
1. Ruler
2. Desk
3. Table
4. Notebook
5. Folder

# data[].attributes.body
1. Blue
2. Green
3. Black
4. Purple
5. Orange

# data[].attributes.body
Between
Under
On
In front of
Behind
Next to

# data[].attributes.body
1. Argentina / Argentinan.
2. Canada/canadian.
3. Brazil/ brazilian.

# data[].attributes.body
CANADA- CANADIAN
ITALY- ITALIAN
BRAZIL - BRAZILIAN

# data[].attributes.body
1 Black
2Pink
3orange
4Green
5 Gray

# data[].attributes.body
architect
teacher
doctor
nurse
lawyer

# data[].attributes.body
- Perú- peruvian
- Chile- chilean
-China- chinese

# data[].attributes.body
1.- Book
2.- Rucksack
3.- Highligters
4.- Pencil
5.- Folders

# data[].attributes.body
1. Blackboard.
2. Chair.
3. Table.
4. Desk.
5. Lectern.

# data[].attributes.body
RULES
DESK
TABLE
COMPUTER
LAPTOP
BOOKS

# data[].attributes.body
- Note book
-Clock
-Desk
-Pencils
-Board

# data[].attributes.body
1. nurse
2. engineer
3. doctor

# data[].attributes.body
1. Perú - Peruvian
2. Chile - Chilean
3. Brazil - Brazilian

# data[].attributes.body
1. Nurse
2. Doctor
3. Engineer
4. Professor
5. Police

# data[].attributes.body
Japan - Japanese
China- Chinese
Canada - canadian

# data[].attributes.body
doctor
engineer
attorney

# data[].attributes.body
Italy Italian
china     chinese
argentine      argentinian

# data[].attributes.body
1. Canada- canadian
2.Germany- German
3.Spain-Spanish

# data[].attributes.body
1. eraser
2. pens
3. pencil
4. planner
5. ruck sack

# data[].attributes.body
1. Pencil
2. Board
3. Table
4. chair
5. Book

# data[].attributes.body
1. Peru - Peruvian
2. Brazil - Brazilian
3. Japan - Japanese
4. Argentina - Argentinian
5. China - Chinese

# data[].attributes.body
1. blue
2. red
3. orange
4. green
5. white

# data[].attributes.body
rucksack
pencil
brush
ruler
eraser

# data[].attributes.body
1.- Red
2.- Blue
3.- Brown
4.- White
5.- Black

# data[].attributes.body
1. Ruler
2. Desk
3. Book
4. Table
5. Blackboard

# data[].attributes.body
1. in
2. on
3. under
4. next to
5. between

# data[].attributes.body
1. ruler
2. pencil
3. bag
4. notebook
5. pencil case

# data[].attributes.body
above
across
along
around

# data[].attributes.body
1. Police
2. doctor
3. teacher

# data[].attributes.body
Colombi-colombian
Peru-Peruvian
Canada-Canadian

# data[].attributes.body
pencil
eraser
sharpener
whiteboard
computer