user_query: placeholder
tree_str_mr: [__DG_INFORM__ [__ARG_TASK__ get_forecast ] [__ARG_TEMP__ 44 ] [__ARG_TEMP_UNIT__ fahrenheit ] [__ARG_DATE_TIME_RANGE__ [__ARG_COLLOQUIAL__ Tonight ] ] [__ARG_LOCATION__ [__ARG_CITY__ São Paulo ] [__ARG_COUNTRY__ Brazil ] [__ARG_REGION__ São Paulo (state) ] ] ]
response: [__DG_INFORM__ [__ARG_DATE_TIME_RANGE__ [__ARG_COLLOQUIAL__ Tonight ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] S [__ARG_REGION__ __ARG_REGION__ ] Br [__ARG_COUNTRY__ __ARG_COUNTRY__ ] ] t will be <number>  [__ARG_TEMP__ __ARG_TEMP__ ] e [__ARG_TEMP_UNIT__ __ARG_TEMP_UNIT__ ] ]
target: [__DG_INFORM__ [__ARG_DATE_TIME_RANGE__ [__ARG_COLLOQUIAL__ Tonight ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] S [__ARG_REGION__ __ARG_REGION__ ] Br [__ARG_COUNTRY__ __ARG_COUNTRY__ ] ] t will be <number>  [__ARG_TEMP__ __ARG_TEMP__ ] e [__ARG_TEMP_UNIT__ __ARG_TEMP_UNIT__ ] ]
references: [__DG_INFORM__ [__ARG_DATE_TIME_RANGE__ [__ARG_COLLOQUIAL__ Tonight ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] S [__ARG_REGION__ __ARG_REGION__ ] Br [__ARG_COUNTRY__ __ARG_COUNTRY__ ] ] t will be <number>  [__ARG_TEMP__ __ARG_TEMP__ ] e [__ARG_TEMP_UNIT__ __ARG_TEMP_UNIT__ ] ]