diff --git a/pandas/core/construction.py b/pandas/core/construction.py
index 92f94f4424ee8..05e267bf83dd6 100644
--- a/pandas/core/construction.py
+++ b/pandas/core/construction.py
@@ -554,9 +554,8 @@ def sanitize_array(
             # TODO: copy?
             subarr = maybe_convert_platform(data)
             if subarr.dtype == object:
-                # Argument 1 to "maybe_infer_to_datetimelike" has incompatible
-                # type "Union[ExtensionArray, ndarray]"; expected "ndarray"
-                subarr = maybe_infer_to_datetimelike(subarr)  # type: ignore[arg-type]
+                subarr = cast(np.ndarray, subarr)
+                subarr = maybe_infer_to_datetimelike(subarr)
 
     subarr = _sanitize_ndim(subarr, data, dtype, index, allow_2d=allow_2d)
 
@@ -620,9 +619,7 @@ def _sanitize_ndim(
         if is_object_dtype(dtype) and isinstance(dtype, ExtensionDtype):
             # i.e. PandasDtype("O")
 
-            # error: Argument "dtype" to "asarray_tuplesafe" has incompatible type
-            # "Type[object]"; expected "Union[str, dtype[Any], None]"
-            result = com.asarray_tuplesafe(data, dtype=object)  # type: ignore[arg-type]
+            result = com.asarray_tuplesafe(data, dtype=np.dtype("object"))
             cls = dtype.construct_array_type()
             result = cls._from_sequence(result, dtype=dtype)
         else:
diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 40883dd8f747b..03554e67d7931 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -123,9 +123,8 @@ def maybe_convert_platform(
         arr = values
 
     if arr.dtype == object:
-        # error: Argument 1 to "maybe_convert_objects" has incompatible type
-        # "Union[ExtensionArray, ndarray]"; expected "ndarray"
-        arr = lib.maybe_convert_objects(arr)  # type: ignore[arg-type]
+        arr = cast(np.ndarray, arr)
+        arr = lib.maybe_convert_objects(arr)
 
     return arr
 
@@ -1249,13 +1248,12 @@ def astype_array(values: ArrayLike, dtype: DtypeObj, copy: bool = False) -> Arra
             return values.copy()
         return values
 
-    if isinstance(values, ABCExtensionArray):
+    if not isinstance(values, np.ndarray):
+        # i.e. ExtensionArray
         values = values.astype(dtype, copy=copy)
 
     else:
-        # error: Argument 1 to "astype_nansafe" has incompatible type "ExtensionArray";
-        # expected "ndarray"
-        values = astype_nansafe(values, dtype, copy=copy)  # type: ignore[arg-type]
+        values = astype_nansafe(values, dtype, copy=copy)
 
     # in pandas we don't store numpy str dtypes, so convert to object
     if isinstance(dtype, np.dtype) and issubclass(values.dtype.type, str):
@@ -1958,7 +1956,7 @@ def construct_1d_object_array_from_listlike(values: Sized) -> np.ndarray:
 
 
 def construct_1d_ndarray_preserving_na(
-    values: Sequence, dtype: DtypeObj | None = None, copy: bool = False
+    values: Sequence, dtype: np.dtype | None = None, copy: bool = False
 ) -> np.ndarray:
     """
     Construct a new ndarray, coercing `values` to `dtype`, preserving NA.
@@ -2003,17 +2001,9 @@ def construct_1d_ndarray_preserving_na(
             and isinstance(values, np.ndarray)
             and values.dtype.kind == "f"
         ):
-            # Argument 2 to "astype_float_to_int_nansafe" has incompatible
-            # type "Union[dtype[Any], ExtensionDtype]"; expected "dtype[Any]"
-            return astype_float_to_int_nansafe(
-                values, dtype, copy=copy  # type: ignore[arg-type]
-            )
+            return astype_float_to_int_nansafe(values, dtype, copy=copy)
         else:
-            # error: Argument "dtype" to "array" has incompatible type
-            # "Union[dtype[Any], ExtensionDtype, None]"; expected "Union[dtype[Any],
-            # None, type, _SupportsDType, str, Union[Tuple[Any, int], Tuple[Any,
-            # Union[int, Sequence[int]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
-            subarr = np.array(values, dtype=dtype, copy=copy)  # type: ignore[arg-type]
+            subarr = np.array(values, dtype=dtype, copy=copy)
 
     return subarr
 
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index 894abb0fb1776..1ae0be5e5f5bf 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -1165,6 +1165,8 @@ def interval_range(
     if periods is not None:
         periods += 1
 
+    breaks: np.ndarray | TimedeltaIndex | DatetimeIndex
+
     if is_number(endpoint):
         # force consistency between start/end/freq (lower end if freq skips it)
         if com.all_not_none(start, end, freq):
@@ -1190,16 +1192,8 @@ def interval_range(
     else:
         # delegate to the appropriate range function
         if isinstance(endpoint, Timestamp):
-            # error: Incompatible types in assignment (expression has type
-            # "DatetimeIndex", variable has type "ndarray")
-            breaks = date_range(  # type: ignore[assignment]
-                start=start, end=end, periods=periods, freq=freq
-            )
+            breaks = date_range(start=start, end=end, periods=periods, freq=freq)
         else:
-            # error: Incompatible types in assignment (expression has type
-            # "TimedeltaIndex", variable has type "ndarray")
-            breaks = timedelta_range(  # type: ignore[assignment]
-                start=start, end=end, periods=periods, freq=freq
-            )
+            breaks = timedelta_range(start=start, end=end, periods=periods, freq=freq)
 
     return IntervalIndex.from_breaks(breaks, name=name, closed=closed)