PERF: Avoid intermediate `ndarray[object]` array when constructing a pyarrow-backed string data from untyped data

[mroeschke]

In [1]: import pandas as pd

In [2]: pd.Series(["a"]).array
> /pandas/core/construction.py(695)sanitize_array()
-> subarr = maybe_convert_platform(data)
(Pdb) data
['a']
(Pdb) n
> /pandas/core/construction.py(696)sanitize_array()
-> if subarr.dtype == object:
(Pdb) subarr
array(['a'], dtype=object)
(Pdb) c
Out[5]: 
<ArrowStringArray>
['a']
Length: 1, dtype: str

In [3]: pd.Series(["a"], dtype=pd.StringDtype("pyarrow"))
Out[3]: 
0    a
dtype: string

maybe_convert_platform calls construct_1d_object_array_from_listlike to convert the list to ndarray[object] for further inference. I wonder if we can perform type inference without converting to object such that for strings we can pass the list directly to ArrowStringArray._from_sequence_of_strings