BUG: pd.NA acts differently when inside/outside a series/dataframe with object dtype
#### Code Sample, a copy-pastable example if possible

```python
# return pd.NA, cool
pd.NA | pd.NA

# return False, not cool
pd.Series([pd.NA]) | pd.Series([pd.NA])
```
#### Problem description

pd.NA acts differently when inside/outside a series/dataframe may be confusing. It force me to handle each entry of a series/dataframe.


#### Expected Output

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.1.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-91-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : None.None

pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0
Cython           : None
pytest           : 5.3.5
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.12.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.0
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.3.5
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None


</details>
