diff --git a/annif/corpus/skos.py b/annif/corpus/skos.py
index 17d84e692..c64d591de 100644
--- a/annif/corpus/skos.py
+++ b/annif/corpus/skos.py
@@ -11,8 +11,8 @@
     Dict,
     Iterator,
     List,
+    Sequence,
     Set,
-    Tuple,
     Union,
 )
 
@@ -118,7 +118,9 @@ def concepts(self) -> Iterator[URIRef]:
             yield concept
 
     def get_concept_labels(
-        self, concept: URIRef, label_types: Union[Tuple[URIRef, URIRef], List[URIRef]]
+        self,
+        concept: URIRef,
+        label_types: Sequence[URIRef],
     ) -> Union[DefaultDict[str, List[str]], DefaultDict[None, List[str]]]:
         """return all the labels of the given concept with the given label
         properties as a dict-like object where the keys are language codes
diff --git a/annif/eval.py b/annif/eval.py
index 8d0cd5c4c..a41e4d632 100644
--- a/annif/eval.py
+++ b/annif/eval.py
@@ -2,7 +2,7 @@
 from __future__ import annotations
 
 import warnings
-from typing import TYPE_CHECKING, Any, Dict, Iterator, List, Optional, Tuple, Union
+from typing import TYPE_CHECKING, Any, Dict, Iterator, List, Optional, Sequence, Union
 
 import numpy as np
 import scipy.sparse
@@ -90,46 +90,7 @@ def evaluate_many(
         suggestion_batch: Union[
             List[List[SubjectSuggestion]], SuggestionBatch, List[Iterator[Any]]
         ],
-        gold_subject_batch: Union[
-            Tuple[SubjectSet, SubjectSet, SubjectSet],
-            Tuple[SubjectSet, SubjectSet, SubjectSet, SubjectSet],
-            Tuple[SubjectSet, SubjectSet],
-            Tuple[
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-                SubjectSet,
-            ],
-            List[SubjectSet],
-        ],
+        gold_subject_batch: Sequence[SubjectSet],
     ) -> None:
         if not isinstance(suggestion_batch, SuggestionBatch):
             suggestion_batch = SuggestionBatch.from_sequence(
@@ -150,7 +111,7 @@ def _evaluate_samples(
         self,
         y_true: csr_array,
         y_pred: csr_array,
-        metrics: Union[Tuple[str, str], Tuple[()], List[str]] = [],
+        metrics: Sequence[str] = [],
     ) -> Dict[str, Union[np.float64, float, int]]:
         y_pred_binary = y_pred > 0.0
 
@@ -285,7 +246,7 @@ def output_result_per_subject(
 
     def results(
         self,
-        metrics: Union[Tuple[str, str], Tuple[()], List[str]] = [],
+        metrics: Sequence[str] = [],
         results_file: Optional[Union[LazyFile, TextIOWrapper]] = None,
         language: Optional[str] = None,
     ) -> Dict[str, Union[np.float64, float]]: