user_query: placeholder
tree_str_mr: [__DG_INFORM__ [__ARG_TASK__ get_forecast ] [__ARG_TEMP_LOW__ 92 ] [__ARG_TEMP_HIGH__ 104 ] [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ today ] ] [__ARG_LOCATION__ [__ARG_CITY__ São Paulo ] ] ]
response: [__DG_INFORM__ The high [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ today ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] ] was <number>  [__ARG_TEMP_HIGH__ __ARG_TEMP_HIGH__ ] and the low was <number>  [__ARG_TEMP_LOW__ __ARG_TEMP_LOW__ ] ]
target: [__DG_INFORM__ The high [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ today ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] ] was <number>  [__ARG_TEMP_HIGH__ __ARG_TEMP_HIGH__ ] and the low was <number>  [__ARG_TEMP_LOW__ __ARG_TEMP_LOW__ ] ]
references: [__DG_INFORM__ The high [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ today ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] ] was <number>  [__ARG_TEMP_HIGH__ __ARG_TEMP_HIGH__ ] and the low was <number>  [__ARG_TEMP_LOW__ __ARG_TEMP_LOW__ ] ]