diff --git a/pandas/_libs/interval.pyx b/pandas/_libs/interval.pyx
index 6e41ff189592c..a47303ddc93cf 100644
--- a/pandas/_libs/interval.pyx
+++ b/pandas/_libs/interval.pyx
@@ -194,7 +194,7 @@ cdef class IntervalMixin:
                              f"expected {repr(self.closed)}.")
 
 
-cdef _interval_like(other):
+cdef bint _interval_like(other):
     return (hasattr(other, 'left')
             and hasattr(other, 'right')
             and hasattr(other, 'closed'))
diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index 6a9ecfe709847..b2301ab0190c7 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -1059,23 +1059,6 @@ def is_datetime_or_timedelta_dtype(arr_or_dtype) -> bool:
     return _is_dtype_type(arr_or_dtype, classes(np.datetime64, np.timedelta64))
 
 
-def _is_unorderable_exception(e: TypeError) -> bool:
-    """
-    Check if the exception raised is an unorderable exception.
-
-    Parameters
-    ----------
-    e : Exception or sub-class
-        The exception object to check.
-
-    Returns
-    -------
-    bool
-        Whether or not the exception raised is an unorderable exception.
-    """
-    return "'>' not supported between instances of" in str(e)
-
-
 # This exists to silence numpy deprecation warnings, see GH#29553
 def is_numeric_v_string_like(a, b):
     """
diff --git a/pandas/core/series.py b/pandas/core/series.py
index c9684d0985173..9e8bdc099063c 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -33,7 +33,6 @@
     validate_numeric_casting,
 )
 from pandas.core.dtypes.common import (
-    _is_unorderable_exception,
     ensure_platform_int,
     is_bool,
     is_categorical_dtype,
@@ -1005,26 +1004,24 @@ def __setitem__(self, key, value):
         except (KeyError, ValueError):
             values = self._values
             if is_integer(key) and not self.index.inferred_type == "integer":
+                # positional setter
                 values[key] = value
             else:
+                # GH#12862 adding an new key to the Series
                 self.loc[key] = value
 
         except TypeError as e:
             if isinstance(key, tuple) and not isinstance(self.index, MultiIndex):
                 raise ValueError("Can only tuple-index with a MultiIndex") from e
 
-            # python 3 type errors should be raised
-            if _is_unorderable_exception(e):
-                raise IndexError(key) from e
-
             if com.is_bool_indexer(key):
                 key = check_bool_indexer(self.index, key)
                 key = np.asarray(key, dtype=bool)
                 try:
                     self._where(~key, value, inplace=True)
-                    return
                 except InvalidIndexError:
                     self._set_values(key.astype(np.bool_), value)
+                return
 
             else:
                 self._set_with(key, value)
@@ -1044,20 +1041,8 @@ def _set_with(self, key, value):
             indexer = self.index._convert_slice_indexer(key, kind="getitem")
             return self._set_values(indexer, value)
 
-        elif is_scalar(key) and not is_integer(key) and key not in self.index:
-            # GH#12862 adding an new key to the Series
-            # Note: have to exclude integers because that is ambiguously
-            #  position-based
-            self.loc[key] = value
-            return
-
         else:
-            if isinstance(key, tuple):
-                try:
-                    # TODO: no test cases that get here
-                    self._set_values(key, value)
-                except Exception:
-                    pass
+            assert not isinstance(key, tuple)
 
             if is_scalar(key):
                 key = [key]
@@ -1074,7 +1059,7 @@ def _set_with(self, key, value):
                 if self.index.inferred_type == "integer":
                     self._set_labels(key, value)
                 else:
-                    return self._set_values(key, value)
+                    self._set_values(key, value)
             else:
                 self._set_labels(key, value)