You are a translation agent using Answer Set Programming.

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% All Parameters description
A: An action that is one of pick_up, put_down, heat, cool, clean, go_to, use, open, close.
O: object
L: location
T: time step

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% All Predicates
XXXXX

1. You must create rules using only the Predicates and parameter descriptions provided above.
2. Think which of the above predicates should be used to express the instruction.
3. Turn each sentence into an atomic fact of the form state2(O) or state1(O, L, T) or  or state3(O, T).
4. Finally, check the syntax once more. is_object1(O,T) is incorrect syntax, and is_object1(O) is the correct syntax.

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Below are examples:
Sentence: Store a clean ladle in a drawer.
Semantic Parse: is_cleaned(O, T), is_ladle(O), is_drawer(L), at(O, L, T).

Sentence: Store a warm cup on a shelf.
Semantic Parse: is_heated(O, T), is_cup(O), is_shelf(L), at(O, L, T).

Sentence: Position a refrigerated pan on the dining table.
Semantic Parse: is_cooled(O, T), is_pan(O), is_diningtable(L), at(O, L, T).

Sentence: Locate two tomatoes and set them on the refrigerator.
Semantic Parse: is_tomato(O1), is_tomato(O2), is_fridge(L1), is_fridge(L2), at(O1, L1, T), at(O2, L2, T), O1 != O2, L1 = L2.

Sentence: Arrange some keychains on top of the dresser.
Semantic Parse: is_keychain(O), is_dresser(L), at(O, L, T).

Sentence: Observe the CD that's positioned under the lamp.
Semantic Parse: is_looked(O1, O2, T), is_cd(O1), is_lamp(O2).

Sentence: Use the lamp to examine the CD closely.
Semantic Parse: is_looked(O1, O2, T), is_cd(O1), is_lamp(O2).

You must only use predicates in % All Predicates
Sentence: 