diff --git a/complex_tokenization/graphs/units.py b/complex_tokenization/graphs/units.py
index 9407b1c..1a7c8de 100644
--- a/complex_tokenization/graphs/units.py
+++ b/complex_tokenization/graphs/units.py
@@ -1,7 +1,31 @@
+from collections.abc import Callable
+
 import regex
 
 from complex_tokenization.graph import GraphVertex, Node, NodesSequence
 
+_cluster_handlers: dict[str, Callable[[str], GraphVertex]] = {}
+
+
+def register_script(script: str, handler: Callable[[str], GraphVertex]):
+    """Register a handler for grapheme clusters matching a Unicode script.
+
+    The script name must be a valid Unicode script property (e.g. "Han",
+    "Hebrew"). When utf8_clusters processes a cluster whose first character
+    matches the script, the handler is called instead of the default utf8.
+    """
+    _cluster_handlers[script] = handler
+
+
+def _get_handler(cluster: str) -> Callable[[str], GraphVertex] | None:
+    if not _cluster_handlers:
+        return None
+    first_char = cluster[0]
+    for script, handler in _cluster_handlers.items():
+        if regex.match(rf'\p{{{script}}}', first_char):
+            return handler
+    return None
+
 
 def characters(s: str) -> GraphVertex:
     nodes = [Node(c.encode("utf-8")) for c in s]
@@ -20,10 +44,14 @@ def utf8(s: str) -> GraphVertex:
 
 
 def utf8_clusters(s: str) -> GraphVertex:
-    # Split string into grapheme clusters using regex
-    # \X matches extended grapheme clusters
     clusters = regex.findall(r'\X', s)
-    nodes = [utf8(cluster) for cluster in clusters]
+    nodes = []
+    for cluster in clusters:
+        handler = _get_handler(cluster)
+        if handler is not None:
+            nodes.append(handler(cluster))
+        else:
+            nodes.append(utf8(cluster))
 
     if len(nodes) == 1:
         return nodes[0]
diff --git a/complex_tokenization/languages/chinese/graph.py b/complex_tokenization/languages/chinese/graph.py
new file mode 100644
index 0000000..746ecd1
--- /dev/null
+++ b/complex_tokenization/languages/chinese/graph.py
@@ -0,0 +1,31 @@
+"""Convert Chinese characters into graph structures using IDS decomposition."""
+
+from complex_tokenization.graph import GraphVertex, Tree
+from complex_tokenization.graphs.units import utf8
+from complex_tokenization.languages.chinese.ideographic_description_sequences import (
+    IDSNode,
+    get_ids_for_character,
+    parse_ideographic_description_sequences,
+)
+
+
+def ids_node_to_graph(node: IDSNode) -> GraphVertex:
+    if node.is_leaf():
+        return utf8(node.value)
+
+    root = utf8(node.value)
+    children = tuple(ids_node_to_graph(child) for child in node.children)
+    return Tree(root=root, children=children)
+
+
+def chinese_character_to_graph(cluster: str) -> GraphVertex:
+    """Convert a Chinese character cluster to a graph, decomposing via IDS if possible."""
+    if len(cluster) == 1:
+        ids = get_ids_for_character(cluster)
+        if ids is not None:
+            try:
+                tree = parse_ideographic_description_sequences(ids)
+                return ids_node_to_graph(tree)
+            except ValueError:
+                pass
+    return utf8(cluster)
diff --git a/complex_tokenization/languages/hebrew/decompose.py b/complex_tokenization/languages/hebrew/decompose.py
index 441444b..e238bca 100644
--- a/complex_tokenization/languages/hebrew/decompose.py
+++ b/complex_tokenization/languages/hebrew/decompose.py
@@ -1,4 +1,4 @@
-"""Decompose Hebrew text into graph structure.
+"""Decompose Hebrew grapheme clusters into graph structure.
 
 Each grapheme cluster becomes:
 - A NodesSequence of [base_letter, diacritics_graph]
@@ -8,8 +8,6 @@
 
 import unicodedata
 
-import regex
-
 from complex_tokenization.graph import FullyConnectedGraph, GraphVertex, NodesSequence
 from complex_tokenization.graphs.units import utf8
 
@@ -48,13 +46,3 @@ def decompose_cluster(cluster: str) -> GraphVertex:
         return diacritics
 
     return NodesSequence(nodes=(base_node, diacritics))
-
-
-def hebrew_grapheme_clusters(text: str) -> GraphVertex:
-    """Convert Hebrew text to a graph using grapheme cluster decomposition."""
-    clusters = regex.findall(r'\X', text)
-    nodes = [decompose_cluster(c) for c in clusters]
-
-    if len(nodes) == 1:
-        return nodes[0]
-    return NodesSequence(nodes=tuple(nodes))
diff --git a/tests/conftest.py b/tests/conftest.py
index 833776e..84c4e23 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,6 +1,7 @@
 import pytest
 
 from complex_tokenization.graphs.settings import GraphSettings
+from complex_tokenization.graphs.units import _cluster_handlers
 
 
 @pytest.fixture(autouse=True)
@@ -12,3 +13,10 @@ def reset_graph_settings():
     yield
     GraphSettings.MAX_MERGE_SIZE = original["MAX_MERGE_SIZE"]
     GraphSettings.ONLY_MINIMAL_MERGES = original["ONLY_MINIMAL_MERGES"]
+
+
+@pytest.fixture(autouse=True)
+def clear_script_registry():
+    _cluster_handlers.clear()
+    yield
+    _cluster_handlers.clear()
diff --git a/tests/languages/test_chinese_training.py b/tests/languages/test_chinese_training.py
new file mode 100644
index 0000000..0a21561
--- /dev/null
+++ b/tests/languages/test_chinese_training.py
@@ -0,0 +1,73 @@
+"""Test training a tokenizer on Chinese text with IDS decomposition."""
+
+from complex_tokenization.graph import Node, NodesSequence, Tree
+from complex_tokenization.graphs.settings import GraphSettings
+from complex_tokenization.graphs.units import register_script, utf8_clusters
+from complex_tokenization.languages.chinese.graph import chinese_character_to_graph
+from complex_tokenization.trainer import Trainer
+
+
+class TestChineseGraph:
+    def test_decomposable_character(self):
+        graph = chinese_character_to_graph("林")
+        assert isinstance(graph, Tree)
+        assert bytes(graph.root) == "⿰".encode()
+
+    def test_non_decomposable_character(self):
+        graph = chinese_character_to_graph("a")
+        assert isinstance(graph, Node)
+
+    def test_chinese_text_via_registry(self):
+        register_script("Han", chinese_character_to_graph)
+        graph = utf8_clusters("林木")
+        assert isinstance(graph, NodesSequence)
+        assert bytes(graph) == "⿰木木木".encode()
+
+    def test_mixed_text_via_registry(self):
+        register_script("Han", chinese_character_to_graph)
+        graph = utf8_clusters("hello")
+        assert bytes(graph) == b"hello"
+
+
+class TestChineseTraining:
+    def test_train_on_repeated_characters(self):
+        register_script("Han", chinese_character_to_graph)
+        GraphSettings.ONLY_MINIMAL_MERGES = True
+        GraphSettings.MAX_MERGE_SIZE = 2
+
+        texts = ["林森木本末朱机杏"] * 3
+        graphs = tuple(utf8_clusters(t) for t in texts)
+        trainer = Trainer(graphs=graphs)
+        trainer.train(num_merges=5)
+
+        assert len(trainer.get_merges()) > 0
+
+    def test_train_on_mixed_chinese_text(self):
+        register_script("Han", chinese_character_to_graph)
+        GraphSettings.ONLY_MINIMAL_MERGES = True
+        GraphSettings.MAX_MERGE_SIZE = 2
+
+        texts = ["你好世界 hello 你好"]
+        graphs = tuple(utf8_clusters(t) for t in texts)
+        trainer = Trainer(graphs=graphs)
+        trainer.train(num_merges=3)
+        assert len(trainer.merges) <= 3
+
+    def test_common_radicals_merge_early(self):
+        register_script("Han", chinese_character_to_graph)
+        GraphSettings.ONLY_MINIMAL_MERGES = True
+        GraphSettings.MAX_MERGE_SIZE = 2
+
+        texts = ["林森林森林森"] * 5
+        graphs = tuple(utf8_clusters(t) for t in texts)
+        trainer = Trainer(graphs=graphs)
+        trainer.train(num_merges=20)
+
+        merge_bytes = [
+            b"".join(bytes(n) for n in nodes)
+            for _, nodes in trainer.merges
+        ]
+        wood = "木".encode()
+        assert any(wood in mb for mb in merge_bytes), (
+            "Expected '木' in merge bytes within 20 merges"
+        )
diff --git a/tests/languages/test_hebrew.py b/tests/languages/test_hebrew.py
index d885557..de08197 100644
--- a/tests/languages/test_hebrew.py
+++ b/tests/languages/test_hebrew.py
@@ -1,16 +1,14 @@
 import unicodedata
 
 from complex_tokenization.graph import FullyConnectedGraph, Node, NodesSequence
-from complex_tokenization.languages.hebrew.decompose import (
-    decompose_cluster,
-    hebrew_grapheme_clusters,
-)
+from complex_tokenization.graphs.units import register_script, utf8_clusters
+from complex_tokenization.languages.hebrew.decompose import decompose_cluster
 
 
 class TestDecomposeCluster:
     def test_bare_letter(self):
         result = decompose_cluster("א")
-        assert isinstance(result, NodesSequence) or isinstance(result, Node)
+        assert isinstance(result, (NodesSequence, Node))
         assert bytes(result) == "א".encode()
 
     def test_letter_with_one_mark(self):
@@ -43,42 +41,39 @@ def test_single_mark_collapses(self):
         base, mark = result.nodes
         assert not isinstance(mark, FullyConnectedGraph)
 
+    def test_fully_connected_merges(self):
+        cluster = "בְּ"  # bet + sheva + dagesh
+        result = decompose_cluster(cluster)
+        merges = list(result.get_merges())
+        merge_bytes = [b"".join(bytes(n) for n in m) for m in merges]
+        sheva = "ְ".encode()
+        dagesh = "ּ".encode()
+        assert sheva + dagesh in merge_bytes
+        assert dagesh + sheva in merge_bytes
+
+
+class TestHebrewViaRegistry:
     def test_bytes_roundtrip(self):
+        register_script("Hebrew", decompose_cluster)
         word = "בְּרֵאשִׁ֖ית"
-        graph = hebrew_grapheme_clusters(word)
+        graph = utf8_clusters(word)
         assert bytes(graph) == word.encode()
 
-
-class TestHebrewGraphemeClusters:
     def test_simple_word(self):
-        result = hebrew_grapheme_clusters("שלום")
+        register_script("Hebrew", decompose_cluster)
+        result = utf8_clusters("שלום")
         assert isinstance(result, NodesSequence)
         assert bytes(result) == "שלום".encode()
 
     def test_word_with_nikkud(self):
-        word = "שָׁלוֹם"  # shalom with nikkud
-        result = hebrew_grapheme_clusters(word)
+        register_script("Hebrew", decompose_cluster)
+        word = "שָׁלוֹם"
+        result = utf8_clusters(word)
         assert isinstance(result, NodesSequence)
         assert bytes(result) == word.encode()
 
-    def test_bereshit_structure(self):
-        word = "בְּרֵאשִׁ֖ית"
-        result = hebrew_grapheme_clusters(word)
-        assert isinstance(result, NodesSequence)
-
     def test_mark_categories(self):
-        """Verify that we correctly identify all Hebrew mark types."""
-        marks = "ְִֵּׁ֖"
+        marks = "ְִֵּׁ֖"
         for ch in marks:
             cat = unicodedata.category(ch)
             assert cat == "Mn", f"{ch!r} (U+{ord(ch):04X}) is {cat}, not Mn"
-
-    def test_fully_connected_merges(self):
-        cluster = "בְּ"  # bet + sheva + dagesh
-        result = decompose_cluster(cluster)
-        merges = list(result.get_merges())
-        merge_bytes = [b"".join(bytes(n) for n in m) for m in merges]
-        sheva = "ְ".encode()
-        dagesh = "ּ".encode()
-        assert sheva + dagesh in merge_bytes
-        assert dagesh + sheva in merge_bytes