diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 9197d839..b56768a3 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -25,7 +25,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.14", "3.10"]
+        python-version: ["3.14", "3.11"]
         tox-command: ["lint", "pyroma", "mypy"]
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
@@ -79,7 +79,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: ["3.14", "3.10"]
+        python-version: ["3.14", "3.11"]
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
       - name: "Install uv"
diff --git a/pyproject.toml b/pyproject.toml
index 7538728d..62844aa1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -27,7 +27,6 @@ classifiers = [
     "Framework :: Sphinx",
     "Natural Language :: English",
     "Programming Language :: Python",
-    "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
@@ -54,14 +53,14 @@ license-files = [
     "LICENSE",
 ]
 
-requires-python = ">=3.10"
+requires-python = ">=3.11"
 dependencies = [
     "click",
     "tqdm",
     "curies>=0.13.0",
     "bioregistry>=0.13.0",
     "sssom-pydantic>=0.5.1",
-    "sssom-curator[web]>=0.4.0",
+    "sssom-curator[predict-lexical,web]>=0.5.0",
 ]
 
 # see https://peps.python.org/pep-0735/ and https://docs.astral.sh/uv/concepts/dependencies/#dependency-groups
diff --git a/scripts/generate_vaccine_mappings.py b/scripts/generate_vaccine_mappings.py
index c3e85f1f..878d3a99 100644
--- a/scripts/generate_vaccine_mappings.py
+++ b/scripts/generate_vaccine_mappings.py
@@ -3,6 +3,7 @@
 import click
 import pyobo
 import ssslm
+from bioregistry import NormalizedNamableReference
 from curies.vocabulary import exact_match, lexical_matching_process
 from pyobo.sources.cpt import iter_terms
 from sssom_pydantic import MappingTool, SemanticMapping
@@ -20,7 +21,9 @@ def main() -> None:
     append_lexical_predictions("cpt", ["mesh", "vo"], mapping_tool=provenance)
 
     preds = []
-    grounder: ssslm.Grounder = pyobo.get_grounder(["mesh", "vo"], versions=["2023", None])
+    grounder: ssslm.Grounder[NormalizedNamableReference] = pyobo.get_grounder(
+        ["mesh", "vo"], versions=["2023", None]
+    )
     for term in iter_terms():
         texts = [term.name, *(s.name for s in term.synonyms)]
         for text in texts:
diff --git a/scripts/generate_vo_mesh_mappings.py b/scripts/generate_vo_mesh_mappings.py
index e463c001..37bbc7e1 100644
--- a/scripts/generate_vo_mesh_mappings.py
+++ b/scripts/generate_vo_mesh_mappings.py
@@ -21,7 +21,7 @@
 
 def main() -> None:
     """Generate mappings from between VO and MeSH."""
-    mesh_grounder = pyobo.get_grounder("mesh")
+    mesh_grounder: ssslm.Grounder[NormalizedNamableReference] = pyobo.get_grounder("mesh")
     provenance = get_script_url(__file__)
     graph = bioontologies.get_obograph_by_prefix("vo", check=False).guess("vo").standardize()
     rows = []
@@ -77,7 +77,10 @@ def main() -> None:
 
 
 def _ground(
-    grounder: ssslm.Grounder, node: Node, rows: list[SemanticMapping], provenance: str
+    grounder: ssslm.Grounder[NormalizedNamableReference],
+    node: Node,
+    rows: list[SemanticMapping],
+    provenance: str,
 ) -> None:
     if not node.reference:
         return None
diff --git a/src/biomappings/paper_analysis.py b/src/biomappings/paper_analysis.py
index 6b036ffe..ddf068a1 100644
--- a/src/biomappings/paper_analysis.py
+++ b/src/biomappings/paper_analysis.py
@@ -10,6 +10,7 @@
 from collections.abc import Iterable, Mapping
 from dataclasses import dataclass
 from pathlib import Path
+from typing import Self
 
 import bioontologies
 import bioregistry
@@ -18,7 +19,6 @@
 from bioregistry import NormalizedReference
 from tabulate import tabulate
 from tqdm.auto import tqdm
-from typing_extensions import Self
 
 __all__ = [
     "Result",