diff --git a/CHANGELOG.md b/CHANGELOG.md
index 390b32e26..73f962d03 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -2,6 +2,9 @@
 
 ## Next
 
+### Added
+- Added a new semantic match resolver to the KG Builder for entity resolution based on spaCy embeddings and cosine similarities so that nodes with similar textual properties get merged.
+
 ## 1.6.0
 
 ### Added
diff --git a/docs/source/api.rst b/docs/source/api.rst
index f27bf3af7..034ef615a 100644
--- a/docs/source/api.rst
+++ b/docs/source/api.rst
@@ -104,6 +104,11 @@ SinglePropertyExactMatchResolver
 .. autoclass:: neo4j_graphrag.experimental.components.resolver.SinglePropertyExactMatchResolver
     :members: run
 
+SpaCySemanticMatchResolver
+================================
+
+.. autoclass:: neo4j_graphrag.experimental.components.resolver.SpaCySemanticMatchResolver
+    :members: run
 
 .. _pipeline-section:
 
diff --git a/docs/source/index.rst b/docs/source/index.rst
index ae8c25d6c..f36e884c5 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -99,7 +99,8 @@ List of extra dependencies:
     - **qdrant**: store vectors in Qdrant
 - **experimental**: experimental features mainly from the Knowledge Graph creation pipelines.
     - Warning: this requires `pygraphviz`. Installation instructions can be found `here <https://pygraphviz.github.io/documentation/stable/install.html>`_.
-
+- nlp:
+   - **spaCy**: load spaCy trained models for nlp pipelines, used by `SpaCySemanticMatchResolver` component from the Knowledge Graph creation pipelines.
 
 ********
 Examples
diff --git a/docs/source/user_guide_kg_builder.rst b/docs/source/user_guide_kg_builder.rst
index 20a7db63f..5bbe11095 100644
--- a/docs/source/user_guide_kg_builder.rst
+++ b/docs/source/user_guide_kg_builder.rst
@@ -1028,22 +1028,28 @@ without making assumptions about entity similarity. The Entity Resolver
 is responsible for refining the created knowledge graph by merging entity
 nodes that represent the same real-world object.
 
-In practice, this package implements a simple resolver that merges nodes
-with the same label and identical "name" property.
+In practice, this package implements two resolvers:
+
+- a simple resolver that merges nodes with the same label and identical "name" property;
+- a semantic match resolver that merges nodes with the same label and similar set of textual properties (by default it uses the "name" property).
+So far, the semantic matching is based on spaCy embeddings and cosine similarities of embedding vectors.
 
 .. warning::
 
-    The `SinglePropertyExactMatchResolver` **replaces** the nodes created by the KG writer.
+    - The `SinglePropertyExactMatchResolver` and `SpaCySemanticMatchResolver` **replace** the nodes created by the KG writer.
+
+    - Check the :ref:`installation` section to make sure you have the required dependencies installed when using `SpaCySemanticMatchResolver`.
 
 
-It can be used like this:
+The resolvers can be used like this:
 
 .. code:: python
 
     from neo4j_graphrag.experimental.components.resolver import (
         SinglePropertyExactMatchResolver,
     )
-    resolver = SinglePropertyExactMatchResolver(driver)
+    resolver = SinglePropertyExactMatchResolver(driver)  # exact match resolver
+    # resolver = SpaCySemanticMatchResolver(driver)  # semantic match with spaCy
     res = await resolver.run()
 
 .. warning::
diff --git a/examples/README.md b/examples/README.md
index 3dd6ee65c..e4759a456 100644
--- a/examples/README.md
+++ b/examples/README.md
@@ -126,8 +126,8 @@ are listed in [the last section of this file](#customize).
   - [Neo4j writer](./customize/build_graph/components/writers/neo4j_writer.py)
   - [Custom](./customize/build_graph/components/writers/custom_writer.py)
 - Entity Resolver:
-  - [SinglePropertyExactMatchResolver](./customize/build_graph/components/resolvers/simple_entity_resolver.py)
   - [SinglePropertyExactMatchResolver with pre-filter](./customize/build_graph/components/resolvers/simple_entity_resolver_pre_filter.py)
+  - [SpaCySemanticMatchResolver with pre-filter](./customize/build_graph/components/resolvers/spacy_entity_resolver_pre_filter.py)
   - [Custom resolver](./customize/build_graph/components/resolvers/custom_resolver.py)
 - [Custom component](./customize/build_graph/components/custom_component.py)
 
diff --git a/examples/customize/build_graph/components/resolvers/simple_entity_resolver.py b/examples/customize/build_graph/components/resolvers/simple_entity_resolver.py
deleted file mode 100644
index 49a4da398..000000000
--- a/examples/customize/build_graph/components/resolvers/simple_entity_resolver.py
+++ /dev/null
@@ -1,25 +0,0 @@
-"""The SinglePropertyExactMatchResolver merge nodes with same label
-and exact same property value (by default using the "name" property).
-
-WARNING: this process is destructive, initial nodes are deleted and replaced
-by the resolved ones, but all relationships are kept.
-See apoc.refactor.mergeNodes documentation for more details.
-"""
-
-import neo4j
-from neo4j_graphrag.experimental.components.resolver import (
-    SinglePropertyExactMatchResolver,
-)
-from neo4j_graphrag.experimental.components.types import ResolutionStats
-
-
-async def main(driver: neo4j.Driver) -> None:
-    resolver = SinglePropertyExactMatchResolver(
-        driver,
-        # optionally, change the property used for resolution (default is "name")
-        # resolve_property="name",
-        # and the neo4j database where data is updated
-        # neo4j_database="neo4j",
-    )
-    res: ResolutionStats = await resolver.run()
-    print(res)
diff --git a/examples/customize/build_graph/components/resolvers/spacy_entity_resolver_pre_filter.py b/examples/customize/build_graph/components/resolvers/spacy_entity_resolver_pre_filter.py
new file mode 100644
index 000000000..2da7ed062
--- /dev/null
+++ b/examples/customize/build_graph/components/resolvers/spacy_entity_resolver_pre_filter.py
@@ -0,0 +1,37 @@
+"""The SpaCySemanticMatchResolver merges nodes with same label
+and similar textual properties (by default using the "name" property) based on spaCy
+embeddings and cosine similarities of embedding vectors.
+
+If the resolution is intended to be applied only on some nodes, for instance nodes that
+belong to a specific document, a "WHERE" query can be added. The only variable in the
+query scope is "entity".
+
+WARNING: this process is destructive, initial nodes are deleted and replaced
+by the resolved ones, but all relationships are kept.
+See apoc.refactor.mergeNodes documentation for more details.
+"""
+
+import neo4j
+from neo4j_graphrag.experimental.components.resolver import (
+    SpaCySemanticMatchResolver,
+)
+from neo4j_graphrag.experimental.components.types import ResolutionStats
+
+
+async def main(driver: neo4j.Driver) -> None:
+    resolver = SpaCySemanticMatchResolver(
+        driver,
+        # let's filter all entities that belong to a certain docId
+        filter_query="WHERE (entity)-[:FROM_CHUNK]->(:Chunk)-[:FROM_DOCUMENT]->(doc:"
+        "Document {id = 'docId'}",
+        # optionally, change the properties used for resolution (default is "name")
+        # resolve_properties=["name", "ssn"],
+        # the similarity threshold (default is 0.8)
+        # similarity_threshold=0.9
+        # the spaCy trained model (default is "en_core_web_lg")
+        # spacy_model="en_core_web_sm"
+        # and the neo4j database where data is updated
+        # neo4j_database="neo4j",
+    )
+    res: ResolutionStats = await resolver.run()
+    print(res)
diff --git a/poetry.lock b/poetry.lock
index 9f3b1f7a3..e6d2c2296 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,104 +1,104 @@
-# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.5.0"
+version = "2.6.1"
 description = "Happy Eyeballs for asyncio"
 optional = true
 python-versions = ">=3.9"
 files = [
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-    {file = "aiohappyeyeballs-2.5.0.tar.gz", hash = "sha256:18fde6204a76deeabc97c48bdd01d5801cfda5d6b9c8bbeb1aaaee9d648ca191"},
+    {file = "aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8"},
+    {file = "aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558"},
 ]
 
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+    {file = "aiohttp-3.11.14-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a8b0321e40a833e381d127be993b7349d1564b756910b28b5f6588a159afef3"},
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+    {file = "aiohttp-3.11.14-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:7f2dadece8b85596ac3ab1ec04b00694bdd62abc31e5618f524648d18d9dd7fa"},
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+    {file = "aiohttp-3.11.14-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a40087b82f83bd671cbeb5f582c233d196e9653220404a798798bfc0ee189fff"},
+    {file = "aiohttp-3.11.14-cp39-cp39-win32.whl", hash = "sha256:95d7787f2bcbf7cb46823036a8d64ccfbc2ffc7d52016b4044d901abceeba3db"},
+    {file = "aiohttp-3.11.14-cp39-cp39-win_amd64.whl", hash = "sha256:22a8107896877212130c58f74e64b77f7007cb03cea8698be317272643602d45"},
+    {file = "aiohttp-3.11.14.tar.gz", hash = "sha256:d6edc538c7480fa0a3b2bdd705f8010062d74700198da55d16498e1b49549b9c"},
 ]
 
 [package.dependencies]
@@ -176,13 +176,13 @@ vertex = ["google-auth (>=2,<3)"]
 
 [[package]]
 name = "anyio"
-version = "4.8.0"
+version = "4.9.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = true
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.8.0-py3-none-any.whl", hash = "sha256:b5011f270ab5eb0abf13385f851315585cc37ef330dd88e27ec3d34d651fd47a"},
-    {file = "anyio-4.8.0.tar.gz", hash = "sha256:1d9fe889df5212298c0c0723fa20479d1b94883a2df44bd3897aa91083316f7a"},
+    {file = "anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c"},
+    {file = "anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028"},
 ]
 
 [package.dependencies]
@@ -192,8 +192,8 @@ sniffio = ">=1.1"
 typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""}
 
 [package.extras]
-doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"]
+doc = ["Sphinx (>=8.2,<9.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"]
+test = ["anyio[trio]", "blockbuster (>=1.5.23)", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"]
 trio = ["trio (>=0.26.1)"]
 
 [[package]]
@@ -245,20 +245,20 @@ files = [
 
 [[package]]
 name = "attrs"
-version = "25.1.0"
+version = "25.3.0"
 description = "Classes Without Boilerplate"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "attrs-25.1.0-py3-none-any.whl", hash = "sha256:c75a69e28a550a7e93789579c22aa26b0f5b83b75dc4e08fe092980051e1090a"},
-    {file = "attrs-25.1.0.tar.gz", hash = "sha256:1c97078a80c814273a76b2a298a932eb681c87415c11dee0a6921de7f1b02c3e"},
+    {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"},
+    {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"},
 ]
 
 [package.extras]
 benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
-docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
+docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier"]
 tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
 
@@ -326,6 +326,47 @@ charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
+[[package]]
+name = "blis"
+version = "1.2.0"
+description = "The Blis BLAS-like linear algebra library, as a self-contained C-extension."
+optional = true
+python-versions = "<3.13,>=3.6"
+files = [
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+    {file = "blis-1.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7d94255f50f54c98727e57d12beeb3cb9d8879fd895d2e8c61d1b975ac87685f"},
+    {file = "blis-1.2.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:6f2ce3b35a66dc7ffff3f68b60a4eb622dbcb0128617c79bf02c098077e2745c"},
+    {file = "blis-1.2.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:f4bdcd436eb08c541c9d44315db2647a30492091cd98a9651a4fe58460a091a3"},
+    {file = "blis-1.2.0-cp39-cp39-win_amd64.whl", hash = "sha256:613a343acad0a254ab87e1b5ec92a031aef73c0640df1e1d09f0f27293654859"},
+    {file = "blis-1.2.0.tar.gz", hash = "sha256:f25f99d7f3cad72c86a7499212ee833fb5062d80ad1763a935e0e498bc147c69"},
+]
+
+[package.dependencies]
+numpy = {version = ">=1.19.0,<3.0.0", markers = "python_version >= \"3.9\""}
+
 [[package]]
 name = "cachecontrol"
 version = "0.14.2"
@@ -358,6 +399,17 @@ files = [
     {file = "cachetools-5.5.2.tar.gz", hash = "sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4"},
 ]
 
+[[package]]
+name = "catalogue"
+version = "2.0.10"
+description = "Super lightweight function registries for your library"
+optional = true
+python-versions = ">=3.6"
+files = [
+    {file = "catalogue-2.0.10-py3-none-any.whl", hash = "sha256:58c2de0020aa90f4a2da7dfad161bf7b3b054c86a5f09fcedc0b2b740c109a9f"},
+    {file = "catalogue-2.0.10.tar.gz", hash = "sha256:4f56daa940913d3f09d589c191c74e5a6d51762b3a9e37dd53b7437afd6cda15"},
+]
+
 [[package]]
 name = "certifi"
 version = "2025.1.31"
@@ -574,6 +626,26 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
+[[package]]
+name = "cloudpathlib"
+version = "0.21.0"
+description = "pathlib-style classes for cloud storage services."
+optional = true
+python-versions = ">=3.9"
+files = [
+    {file = "cloudpathlib-0.21.0-py3-none-any.whl", hash = "sha256:657e95ecd2663f1123b6daa95d49aca4b4bc8a9fa90c07930bdba2c5e295e5ef"},
+    {file = "cloudpathlib-0.21.0.tar.gz", hash = "sha256:fb8f6b890a3d37b35f0eabff86721bb8d35dfc6a6be98c1f4d34b19e989c6641"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">4", markers = "python_version < \"3.11\""}
+
+[package.extras]
+all = ["cloudpathlib[azure]", "cloudpathlib[gs]", "cloudpathlib[s3]"]
+azure = ["azure-storage-blob (>=12)", "azure-storage-file-datalake (>=12)"]
+gs = ["google-cloud-storage"]
+s3 = ["boto3 (>=1.34.0)"]
+
 [[package]]
 name = "cohere"
 version = "5.14.0"
@@ -607,76 +679,91 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "confection"
+version = "0.1.5"
+description = "The sweetest config system for Python"
+optional = true
+python-versions = ">=3.6"
+files = [
+    {file = "confection-0.1.5-py3-none-any.whl", hash = "sha256:e29d3c3f8eac06b3f77eb9dfb4bf2fc6bcc9622a98ca00a698e3d019c6430b14"},
+    {file = "confection-0.1.5.tar.gz", hash = "sha256:8e72dd3ca6bd4f48913cd220f10b8275978e740411654b6e8ca6d7008c590f0e"},
+]
+
+[package.dependencies]
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<3.0.0"
+srsly = ">=2.4.0,<3.0.0"
+
 [[package]]
 name = "coverage"
-version = "7.6.12"
+version = "7.7.0"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.9"
 files = [
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+[[package]]
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+]
+
 [[package]]
 name = "dataclasses-json"
 version = "0.6.7"
@@ -968,13 +1100,13 @@ zstandard = ["zstandard"]
 
 [[package]]
 name = "filelock"
-version = "3.17.0"
+version = "3.18.0"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.extras]
@@ -1155,10 +1287,7 @@ grpcio-status = [
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     {version = ">=1.33.2,<2.0.dev0", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
 ]
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-    {version = ">=1.22.3,<2.0.0", markers = "python_version < \"3.13\""},
-]
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 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 requests = ">=2.18.0,<3.0.0"
 
@@ -1194,27 +1323,27 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.83.0"
+version = "1.85.0"
 description = "Vertex AI API client library"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
 docstring-parser = "<1"
-google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.8.dev0,<3.0.0dev", extras = ["grpc"]}
-google-auth = ">=2.14.1,<3.0.0dev"
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-google-cloud-resource-manager = ">=1.3.3,<3.0.0dev"
-google-cloud-storage = ">=1.32.0,<3.0.0dev"
+google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.8.dev0,<3.0.0", extras = ["grpc"]}
+google-auth = ">=2.14.1,<3.0.0"
+google-cloud-bigquery = ">=1.15.0,<3.20.0 || >3.20.0,<4.0.0"
+google-cloud-resource-manager = ">=1.3.3,<3.0.0"
+google-cloud-storage = ">=1.32.0,<3.0.0"
 packaging = ">=14.3"
-proto-plus = ">=1.22.3,<2.0.0dev"
-protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0dev"
+proto-plus = ">=1.22.3,<2.0.0"
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 pydantic = "<3"
-shapely = "<3.0.0dev"
+shapely = "<3.0.0"
 typing-extensions = "*"
 
 [package.extras]
@@ -1222,14 +1351,14 @@ ag2 = ["ag2[gemini]", "openinference-instrumentation-autogen (>=0.1.6,<0.2)"]
 ag2-testing = ["absl-py", "ag2[gemini]", "cloudpickle (>=3.0,<4.0)", "google-cloud-trace (<2)", "openinference-instrumentation-autogen (>=0.1.6,<0.2)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "pydantic (>=2.6.3,<3)", "pytest-xdist", "typing-extensions"]
 agent-engines = ["cloudpickle (>=3.0,<4.0)", "google-cloud-logging (<4)", "google-cloud-trace (<2)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "packaging (>=24.0)", "pydantic (>=2.10,<3)", "typing-extensions"]
 autologging = ["mlflow (>=1.27.0,<=2.16.0)"]
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-datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)"]
+cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<2.18.0)", "tensorflow (>=2.4.0,<3.0.0)", "werkzeug (>=2.0.0,<2.1.0)"]
+datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0.0)"]
 endpoint = ["requests (>=2.28.1)"]
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+    {file = "google_crc32c-1.7.0-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:731921158ef113bf157b8e65f13303d627fb540f173a410260f2fb7570af644c"},
+    {file = "google_crc32c-1.7.0.tar.gz", hash = "sha256:c8c15a04b290c7556f277acc55ad98503a8bc0893ea6860fd5b5d210f3f558ce"},
 ]
 
 [package.extras]
@@ -1395,21 +1527,21 @@ requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.69.1"
+version = "1.69.2"
 description = "Common protobufs used in Google APIs"
 optional = true
 python-versions = ">=3.7"
 files = [
-    {file = "googleapis_common_protos-1.69.1-py2.py3-none-any.whl", hash = "sha256:4077f27a6900d5946ee5a369fab9c8ded4c0ef1c6e880458ea2f70c14f7b70d5"},
-    {file = "googleapis_common_protos-1.69.1.tar.gz", hash = "sha256:e20d2d8dda87da6fe7340afbbdf4f0bcb4c8fae7e6cadf55926c31f946b0b9b1"},
+    {file = "googleapis_common_protos-1.69.2-py3-none-any.whl", hash = "sha256:0b30452ff9c7a27d80bfc5718954063e8ab53dd3697093d3bc99581f5fd24212"},
+    {file = "googleapis_common_protos-1.69.2.tar.gz", hash = "sha256:3e1b904a27a33c821b4b749fd31d334c0c9c30e6113023d495e48979a3dc9c5f"},
 ]
 
 [package.dependencies]
-grpcio = {version = ">=1.44.0,<2.0.0.dev0", optional = true, markers = "extra == \"grpc\""}
-protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
+grpcio = {version = ">=1.44.0,<2.0.0", optional = true, markers = "extra == \"grpc\""}
+protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 
 [package.extras]
-grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
+grpc = ["grpcio (>=1.44.0,<2.0.0)"]
 
 [[package]]
 name = "greenlet"
@@ -1499,19 +1631,19 @@ test = ["objgraph", "psutil"]
 
 [[package]]
 name = "grpc-google-iam-v1"
-version = "0.14.1"
+version = "0.14.2"
 description = "IAM API client library"
 optional = true
 python-versions = ">=3.7"
 files = [
-    {file = "grpc_google_iam_v1-0.14.1-py2.py3-none-any.whl", hash = "sha256:b4eca35b2231dd76066ebf1728f3cd30d51034db946827ef63ef138da14eea16"},
-    {file = "grpc_google_iam_v1-0.14.1.tar.gz", hash = "sha256:14149f37af0e5779fa8a22a8ae588663269e8a479d9c2e69a5056e589bf8a891"},
+    {file = "grpc_google_iam_v1-0.14.2-py3-none-any.whl", hash = "sha256:a3171468459770907926d56a440b2bb643eec1d7ba215f48f3ecece42b4d8351"},
+    {file = "grpc_google_iam_v1-0.14.2.tar.gz", hash = "sha256:b3e1fc387a1a329e41672197d0ace9de22c78dd7d215048c4c78712073f7bd20"},
 ]
 
 [package.dependencies]
-googleapis-common-protos = {version = ">=1.56.0,<2.0.0dev", extras = ["grpc"]}
-grpcio = ">=1.44.0,<2.0.0dev"
-protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0dev"
+googleapis-common-protos = {version = ">=1.56.0,<2.0.0", extras = ["grpc"]}
+grpcio = ">=1.44.0,<2.0.0"
+protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 
 [[package]]
 name = "grpcio"
@@ -2067,13 +2199,13 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.43"
+version = "0.3.45"
 description = "Building applications with LLMs through composability"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_core-0.3.43-py3-none-any.whl", hash = "sha256:caa6bc1f4c6ab71d3c2e400f8b62e1cd6dc5ac2c37e03f12f3e2c60befd5b273"},
-    {file = "langchain_core-0.3.43.tar.gz", hash = "sha256:bec60f4f5665b536434ff747b8f23375a812e82cfa529f519b54cc1e7a94a875"},
+    {file = "langchain_core-0.3.45-py3-none-any.whl", hash = "sha256:fe560d644c102c3f5dcfb44eb5295e26d22deab259fdd084f6b1b55a0350b77c"},
+    {file = "langchain_core-0.3.45.tar.gz", hash = "sha256:a39b8446495d1ea97311aa726478c0a13ef1d77cb7644350bad6d9d3c0141a0c"},
 ]
 
 [package.dependencies]
@@ -2081,8 +2213,8 @@ jsonpatch = ">=1.33,<2.0"
 langsmith = ">=0.1.125,<0.4"
 packaging = ">=23.2,<25"
 pydantic = [
-    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
     {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
 PyYAML = ">=5.3"
 tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0"
@@ -2124,27 +2256,45 @@ tiktoken = ">=0.7,<1"
 
 [[package]]
 name = "langchain-text-splitters"
-version = "0.3.6"
+version = "0.3.7"
 description = "LangChain text splitting utilities"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_text_splitters-0.3.6-py3-none-any.whl", hash = "sha256:e5d7b850f6c14259ea930be4a964a65fa95d9df7e1dbdd8bad8416db72292f4e"},
-    {file = "langchain_text_splitters-0.3.6.tar.gz", hash = "sha256:c537972f4b7c07451df431353a538019ad9dadff7a1073ea363946cea97e1bee"},
+    {file = "langchain_text_splitters-0.3.7-py3-none-any.whl", hash = "sha256:31ba826013e3f563359d7c7f1e99b1cdb94897f665675ee505718c116e7e20ad"},
+    {file = "langchain_text_splitters-0.3.7.tar.gz", hash = "sha256:7dbf0fb98e10bb91792a1d33f540e2287f9cc1dc30ade45b7aedd2d5cd3dc70b"},
+]
+
+[package.dependencies]
+langchain-core = ">=0.3.45,<1.0.0"
+
+[[package]]
+name = "langcodes"
+version = "3.5.0"
+description = "Tools for labeling human languages with IETF language tags"
+optional = true
+python-versions = ">=3.9"
+files = [
+    {file = "langcodes-3.5.0-py3-none-any.whl", hash = "sha256:853c69d1a35e0e13da2f427bb68fb2fa4a8f4fb899e0c62ad8df8d073dcfed33"},
+    {file = "langcodes-3.5.0.tar.gz", hash = "sha256:1eef8168d07e51e131a2497ffecad4b663f6208e7c3ae3b8dc15c51734a6f801"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.34,<1.0.0"
+language-data = ">=1.2"
+
+[package.extras]
+build = ["build", "twine"]
+test = ["pytest", "pytest-cov"]
 
 [[package]]
 name = "langsmith"
-version = "0.3.13"
+version = "0.3.16"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langsmith-0.3.13-py3-none-any.whl", hash = "sha256:73aaf52bbc293b9415fff4f6dad68df40658081eb26c9cb2c7bd1ff57cedd695"},
-    {file = "langsmith-0.3.13.tar.gz", hash = "sha256:14014058cff408772acb93344e03cb64174837292d5f1ae09b2c8c1d8df45e92"},
+    {file = "langsmith-0.3.16-py3-none-any.whl", hash = "sha256:c8f53b11e68042d2d53db13c91db5e81e2c02974bbaf2218dad34ffd77e45744"},
+    {file = "langsmith-0.3.16.tar.gz", hash = "sha256:dbf22b9426f8ece61089dad825a483db27095904648b8dcd92b620920af6a9ff"},
 ]
 
 [package.dependencies]
@@ -2152,8 +2302,8 @@ httpx = ">=0.23.0,<1"
 orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""}
 packaging = ">=23.2"
 pydantic = [
-    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
     {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
 requests = ">=2,<3"
 requests-toolbelt = ">=1.0.0,<2.0.0"
@@ -2161,17 +2311,36 @@ zstandard = ">=0.23.0,<0.24.0"
 
 [package.extras]
 langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"]
+openai-agents = ["openai-agents (>=0.0.3,<0.0.4)"]
 pytest = ["pytest (>=7.0.0)", "rich (>=13.9.4,<14.0.0)"]
 
+[[package]]
+name = "language-data"
+version = "1.3.0"
+description = "Supplementary data about languages used by the langcodes module"
+optional = true
+python-versions = "*"
+files = [
+    {file = "language_data-1.3.0-py3-none-any.whl", hash = "sha256:e2ee943551b5ae5f89cd0e801d1fc3835bb0ef5b7e9c3a4e8e17b2b214548fbf"},
+    {file = "language_data-1.3.0.tar.gz", hash = "sha256:7600ef8aa39555145d06c89f0c324bf7dab834ea0b0a439d8243762e3ebad7ec"},
+]
+
+[package.dependencies]
+marisa-trie = ">=1.1.0"
+
+[package.extras]
+build = ["build", "twine"]
+test = ["pytest", "pytest-cov"]
+
 [[package]]
 name = "llama-cloud"
-version = "0.1.14"
+version = "0.1.15"
 description = ""
 optional = true
 python-versions = "<4,>=3.8"
 files = [
-    {file = "llama_cloud-0.1.14-py3-none-any.whl", hash = "sha256:187672847dedc018b4d2620a8d26d6bf213e425e8b91569773de48e5c2f3ca5a"},
-    {file = "llama_cloud-0.1.14.tar.gz", hash = "sha256:90741a19ba96967fa2484084928e326ae957736780a15b67bc3ad5f52e94782d"},
+    {file = "llama_cloud-0.1.15-py3-none-any.whl", hash = "sha256:8e7376346d580b244a87d023eb7493506f06b53c898fb2a2e712b9fe7eb5b310"},
+    {file = "llama_cloud-0.1.15.tar.gz", hash = "sha256:3ec98422072ee4290c1e7597bc33889af3f03edb2a50ab09c15d5586d9f8635c"},
 ]
 
 [package.dependencies]
@@ -2181,38 +2350,38 @@ pydantic = ">=1.10"
 
 [[package]]
 name = "llama-cloud-services"
-version = "0.6.5"
+version = "0.6.6"
 description = "Tailored SDK clients for LlamaCloud services."
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_cloud_services-0.6.5-py3-none-any.whl", hash = "sha256:d9d4d0407b03249fea65aa369b110f9ee60601e4c82dba3e0a774f3a997d2b63"},
-    {file = "llama_cloud_services-0.6.5.tar.gz", hash = "sha256:7c00900ed72b199d7118879637a4df060065c70cc0562f3b229e47d5f85bdb7b"},
+    {file = "llama_cloud_services-0.6.6-py3-none-any.whl", hash = "sha256:e08e92b034c1cb67f66e959c3233b5e09e3fba2c86cc8208327b874d8e60fcc5"},
+    {file = "llama_cloud_services-0.6.6.tar.gz", hash = "sha256:4e2ea6f9e632df62da456cbeb9d00665d09886d1caf759241ffa73c7c47d57c8"},
 ]
 
 [package.dependencies]
 click = ">=8.1.7,<9.0.0"
 eval-type-backport = {version = ">=0.2.0,<0.3.0", markers = "python_version < \"3.10\""}
-llama-cloud = ">=0.1.14,<0.2.0"
+llama-cloud = ">=0.1.15,<0.2.0"
 llama-index-core = ">=0.11.0"
 pydantic = "!=2.10"
 python-dotenv = ">=1.0.1,<2.0.0"
 
 [[package]]
 name = "llama-index"
-version = "0.12.23"
+version = "0.12.25"
 description = "Interface between LLMs and your data"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_index-0.12.23-py3-none-any.whl", hash = "sha256:a099e06005f0e776a75b1cbac68af966bd2866c31f868d5c4f4e5be6ba641c60"},
-    {file = "llama_index-0.12.23.tar.gz", hash = "sha256:af1e3b0ecb63c2e6ff95874189ca68e3fcdba19bb312abb7df19c6855cc709c0"},
+    {file = "llama_index-0.12.25-py3-none-any.whl", hash = "sha256:e8c458feccedc6a125a2c04de1d76d84299a7d3c2382ef1d20c64639f42b000a"},
+    {file = "llama_index-0.12.25.tar.gz", hash = "sha256:a4681109fe4cba1a8a17867769a18fc5f4f3deab28c3263c385f172f4cbcb6e4"},
 ]
 
 [package.dependencies]
 llama-index-agent-openai = ">=0.4.0,<0.5.0"
 llama-index-cli = ">=0.4.1,<0.5.0"
-llama-index-core = ">=0.12.23,<0.13.0"
+llama-index-core = ">=0.12.25,<0.13.0"
 llama-index-embeddings-openai = ">=0.3.0,<0.4.0"
 llama-index-indices-managed-llama-cloud = ">=0.4.0"
 llama-index-llms-openai = ">=0.3.0,<0.4.0"
@@ -2257,13 +2426,13 @@ llama-index-llms-openai = ">=0.3.0,<0.4.0"
 
 [[package]]
 name = "llama-index-core"
-version = "0.12.23.post2"
+version = "0.12.25"
 description = "Interface between LLMs and your data"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_index_core-0.12.23.post2-py3-none-any.whl", hash = "sha256:3665583d69ca9859b019aacf9496af29ec2fa3b24d031344ddeeefb0dbd00e26"},
-    {file = "llama_index_core-0.12.23.post2.tar.gz", hash = "sha256:b8e8abc2c11c2fa26bbfeebc79b00d8d12aaba370e43e3450045b50048744b90"},
+    {file = "llama_index_core-0.12.25-py3-none-any.whl", hash = "sha256:affd0b240daf3c1200ad8ca86696ce339f411c3028981b0b5b71b59d78f281ae"},
+    {file = "llama_index_core-0.12.25.tar.gz", hash = "sha256:e0145617f0ab5358c30a7a716fa46dd3c40183bad1b87dd0cbfd3d196fbee8c4"},
 ]
 
 [package.dependencies]
@@ -2308,13 +2477,13 @@ openai = ">=1.1.0"
 
 [[package]]
 name = "llama-index-indices-managed-llama-cloud"
-version = "0.6.8"
+version = "0.6.9"
 description = "llama-index indices llama-cloud integration"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -2433,6 +2602,121 @@ files = [
 [package.dependencies]
 llama-cloud-services = ">=0.6.4"
 
+[[package]]
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+
+[package.dependencies]
+setuptools = "*"
+
+[package.extras]
+test = ["hypothesis", "pytest", "readme-renderer"]
+
+[[package]]
+name = "markdown-it-py"
+version = "3.0.0"
+description = "Python port of markdown-it. Markdown parsing, done right!"
+optional = true
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+mdurl = ">=0.1,<1.0"
+
+[package.extras]
+benchmarking = ["psutil", "pytest", "pytest-benchmark"]
+code-style = ["pre-commit (>=3.0,<4.0)"]
+compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
+linkify = ["linkify-it-py (>=1,<3)"]
+plugins = ["mdit-py-plugins"]
+profiling = ["gprof2dot"]
+rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
+testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
+
 [[package]]
 name = "markupsafe"
 version = "3.0.2"
@@ -2522,6 +2806,17 @@ dev = ["marshmallow[tests]", "pre-commit (>=3.5,<5.0)", "tox"]
 docs = ["autodocsumm (==0.2.14)", "furo (==2024.8.6)", "sphinx (==8.1.3)", "sphinx-copybutton (==0.5.2)", "sphinx-issues (==5.0.0)", "sphinxext-opengraph (==0.9.1)"]
 tests = ["pytest", "simplejson"]
 
+[[package]]
+name = "mdurl"
+version = "0.1.2"
+description = "Markdown URL utilities"
+optional = true
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 [package.dependencies]
 typing-extensions = {version = ">=4.1.0", markers = "python_version < \"3.11\""}
 
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+
 [[package]]
 name = "mypy"
 version = "1.15.0"
@@ -3150,13 +3490,13 @@ pydantic = ">=2.9.0,<3.0.0"
 
 [[package]]
 name = "openai"
-version = "1.65.5"
+version = "1.66.5"
 description = "The official Python library for the openai API"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3325,9 +3665,9 @@ files = [
 
 [package.dependencies]
 numpy = [
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     {version = ">=1.23.2", markers = "python_version == \"3.11\""},
     {version = ">=1.22.4", markers = "python_version < \"3.11\""},
+    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -3463,8 +3803,8 @@ pinecone-plugin-interface = ">=0.0.7,<0.0.8"
 tqdm = ">=4.64.1"
 typing-extensions = ">=3.7.4"
 urllib3 = [
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     {version = ">=1.26.0", markers = "python_version >= \"3.8\" and python_version < \"3.12\""},
+    {version = ">=1.26.5", markers = "python_version >= \"3.12\" and python_version < \"4.0\""},
 ]
 
 [package.extras]
@@ -3549,6 +3889,52 @@ nodeenv = ">=0.11.1"
 pyyaml = ">=5.1"
 virtualenv = ">=20.10.0"
 
+[[package]]
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+version = "3.0.9"
+description = "Cython hash table that trusts the keys are pre-hashed"
+optional = true
+python-versions = ">=3.6"
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+[package.dependencies]
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+murmurhash = ">=0.28.0,<1.1.0"
+
 [[package]]
 name = "propcache"
 version = "0.3.0"
@@ -3731,18 +4117,18 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "2.11.0b1"
+version = "2.11.0b2"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
 annotated-types = ">=0.6.0"
-pydantic-core = "2.31.1"
+pydantic-core = "2.32.0"
 typing-extensions = ">=4.12.2"
 typing-inspection = ">=0.4.0"
 
@@ -3752,110 +4138,110 @@ timezone = ["tzdata"]
 
 [[package]]
 name = "pydantic-core"
-version = "2.31.1"
+version = "2.32.0"
 description = "Core functionality for Pydantic validation and serialization"
 optional = false
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 [package.dependencies]
@@ -3897,13 +4283,13 @@ files = [
 
 [[package]]
 name = "pypdf"
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+version = "5.4.0"
 description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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 [[package]]
 name = "pywin32"
-version = "309"
+version = "310"
 description = "Python for Window Extensions"
 optional = true
 python-versions = "*"
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 [[package]]
@@ -4083,30 +4469,6 @@ files = [
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 ]
 
-[[package]]
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-version = "1.12.1"
-description = "Client library for the Qdrant vector search engine"
-optional = true
-python-versions = ">=3.8"
-files = [
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-grpcio-tools = ">=1.41.0"
-httpx = {version = ">=0.20.0", extras = ["http2"]}
-numpy = {version = ">=1.26", markers = "python_version >= \"3.12\""}
-portalocker = ">=2.7.0,<3.0.0"
-pydantic = ">=1.10.8"
-urllib3 = ">=1.26.14,<3"
-
-[package.extras]
-fastembed = ["fastembed (==0.3.6)"]
-fastembed-gpu = ["fastembed-gpu (==0.3.6)"]
-
 [[package]]
 name = "qdrant-client"
 version = "1.13.3"
@@ -4273,6 +4635,25 @@ files = [
 [package.dependencies]
 requests = ">=2.0.1,<3.0.0"
 
+[[package]]
+name = "rich"
+version = "13.9.4"
+description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
+optional = true
+python-versions = ">=3.8.0"
+files = [
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+
+[package.dependencies]
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+pygments = ">=2.13.0,<3.0.0"
+typing-extensions = {version = ">=4.0.0,<5.0", markers = "python_version < \"3.11\""}
+
+[package.extras]
+jupyter = ["ipywidgets (>=7.5.1,<9)"]
+
 [[package]]
 name = "rsa"
 version = "4.9"
@@ -4548,13 +4929,13 @@ train = ["accelerate (>=0.20.3)", "datasets"]
 
 [[package]]
 name = "setuptools"
-version = "76.0.0"
+version = "76.1.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = true
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.extras]
@@ -4624,6 +5005,17 @@ numpy = ">=1.14,<3"
 docs = ["matplotlib", "numpydoc (==1.1.*)", "sphinx", "sphinx-book-theme", "sphinx-remove-toctrees"]
 test = ["pytest", "pytest-cov"]
 
+[[package]]
+name = "shellingham"
+version = "1.5.4"
+description = "Tool to Detect Surrounding Shell"
+optional = true
+python-versions = ">=3.7"
+files = [
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+]
+
 [[package]]
 name = "six"
 version = "1.17.0"
@@ -4635,6 +5027,31 @@ files = [
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 ]
 
+[[package]]
+name = "smart-open"
+version = "7.1.0"
+description = "Utils for streaming large files (S3, HDFS, GCS, Azure Blob Storage, gzip, bz2...)"
+optional = true
+python-versions = "<4.0,>=3.7"
+files = [
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+]
+
+[package.dependencies]
+wrapt = "*"
+
+[package.extras]
+all = ["azure-common", "azure-core", "azure-storage-blob", "boto3", "google-cloud-storage (>=2.6.0)", "paramiko", "requests", "zstandard"]
+azure = ["azure-common", "azure-core", "azure-storage-blob"]
+gcs = ["google-cloud-storage (>=2.6.0)"]
+http = ["requests"]
+s3 = ["boto3"]
+ssh = ["paramiko"]
+test = ["awscli", "azure-common", "azure-core", "azure-storage-blob", "boto3", "google-cloud-storage (>=2.6.0)", "moto[server]", "numpy", "paramiko", "pyopenssl", "pytest", "pytest-benchmark", "pytest-rerunfailures", "requests", "responses", "zstandard"]
+webhdfs = ["requests"]
+zst = ["zstandard"]
+
 [[package]]
 name = "sniffio"
 version = "1.3.1"
@@ -4668,6 +5085,106 @@ files = [
     {file = "soupsieve-2.6.tar.gz", hash = "sha256:e2e68417777af359ec65daac1057404a3c8a5455bb8abc36f1a9866ab1a51abb"},
 ]
 
+[[package]]
+name = "spacy"
+version = "3.8.3"
+description = "Industrial-strength Natural Language Processing (NLP) in Python"
+optional = true
+python-versions = "<3.13,>=3.9"
+files = [
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 sqlcipher = ["sqlcipher3_binary"]
 
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 ]
 
+[package.dependencies]
+catalogue = ">=2.0.3,<2.1.0"
+
 [[package]]
 name = "striprtf"
 version = "0.0.26"
@@ -5066,15 +5619,85 @@ files = [
 doc = ["reno", "sphinx"]
 test = ["pytest", "tornado (>=4.5)", "typeguard"]
 
+[[package]]
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+]
+
+[package.dependencies]
+blis = ">=1.2.0,<1.3.0"
+catalogue = ">=2.0.4,<2.1.0"
+confection = ">=0.0.1,<1.0.0"
+cymem = ">=2.0.2,<2.1.0"
+murmurhash = ">=1.0.2,<1.1.0"
+numpy = {version = ">=1.19.0,<3.0.0", markers = "python_version >= \"3.9\""}
+packaging = ">=20.0"
+preshed = ">=3.0.2,<3.1.0"
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<3.0.0"
+setuptools = "*"
+srsly = ">=2.4.0,<3.0.0"
+wasabi = ">=0.8.1,<1.2.0"
+
+[package.extras]
+apple = ["thinc-apple-ops (>=1.0.0,<2.0.0)"]
+cuda = ["cupy (>=5.0.0b4)"]
+cuda-autodetect = ["cupy-wheel (>=11.0.0)"]
+cuda100 = ["cupy-cuda100 (>=5.0.0b4)"]
+cuda101 = ["cupy-cuda101 (>=5.0.0b4)"]
+cuda102 = ["cupy-cuda102 (>=5.0.0b4)"]
+cuda110 = ["cupy-cuda110 (>=5.0.0b4)"]
+cuda111 = ["cupy-cuda111 (>=5.0.0b4)"]
+cuda112 = ["cupy-cuda112 (>=5.0.0b4)"]
+cuda113 = ["cupy-cuda113 (>=5.0.0b4)"]
+cuda114 = ["cupy-cuda114 (>=5.0.0b4)"]
+cuda115 = ["cupy-cuda115 (>=5.0.0b4)"]
+cuda116 = ["cupy-cuda116 (>=5.0.0b4)"]
+cuda117 = ["cupy-cuda117 (>=5.0.0b4)"]
+cuda11x = ["cupy-cuda11x (>=11.0.0)"]
+cuda12x = ["cupy-cuda12x (>=11.5.0)"]
+cuda80 = ["cupy-cuda80 (>=5.0.0b4)"]
+cuda90 = ["cupy-cuda90 (>=5.0.0b4)"]
+cuda91 = ["cupy-cuda91 (>=5.0.0b4)"]
+cuda92 = ["cupy-cuda92 (>=5.0.0b4)"]
+datasets = ["ml_datasets (>=0.2.0,<0.3.0)"]
+mxnet = ["mxnet (>=1.5.1,<1.6.0)"]
+tensorflow = ["tensorflow (>=2.0.0,<2.6.0)"]
+torch = ["torch (>=1.6.0)"]
+
 [[package]]
 name = "threadpoolctl"
-version = "3.5.0"
+version = "3.6.0"
 description = "threadpoolctl"
 optional = true
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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 ]
 
 [[package]]
@@ -5126,26 +5749,26 @@ blobfile = ["blobfile (>=2)"]
 
 [[package]]
 name = "tokenizers"
-version = "0.21.0"
+version = "0.21.1"
 description = ""
 optional = true
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
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-    {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d8b09dbeb7a8d73ee204a70f94fc06ea0f17dcf0844f16102b9f414f0b7463ba"},
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+    {file = "tokenizers-0.21.1-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:e78e413e9e668ad790a29456e677d9d3aa50a9ad311a40905d6861ba7692cf41"},
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+    {file = "tokenizers-0.21.1-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:34d8cfde551c9916cb92014e040806122295a6800914bab5865deb85623931cf"},
+    {file = "tokenizers-0.21.1-cp39-abi3-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:aaa852d23e125b73d283c98f007e06d4595732104b65402f46e8ef24b588d9f8"},
+    {file = "tokenizers-0.21.1-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a21a15d5c8e603331b8a59548bbe113564136dc0f5ad8306dd5033459a226da0"},
+    {file = "tokenizers-0.21.1-cp39-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2fdbd4c067c60a0ac7eca14b6bd18a5bebace54eb757c706b47ea93204f7a37c"},
+    {file = "tokenizers-0.21.1-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2dd9a0061e403546f7377df940e866c3e678d7d4e9643d0461ea442b4f89e61a"},
+    {file = "tokenizers-0.21.1-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:db9484aeb2e200c43b915a1a0150ea885e35f357a5a8fabf7373af333dcc8dbf"},
+    {file = "tokenizers-0.21.1-cp39-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:ed248ab5279e601a30a4d67bdb897ecbe955a50f1e7bb62bd99f07dd11c2f5b6"},
+    {file = "tokenizers-0.21.1-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:9ac78b12e541d4ce67b4dfd970e44c060a2147b9b2a21f509566d556a509c67d"},
+    {file = "tokenizers-0.21.1-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:e5a69c1a4496b81a5ee5d2c1f3f7fbdf95e90a0196101b0ee89ed9956b8a168f"},
+    {file = "tokenizers-0.21.1-cp39-abi3-win32.whl", hash = "sha256:1039a3a5734944e09de1d48761ade94e00d0fa760c0e0551151d4dd851ba63e3"},
+    {file = "tokenizers-0.21.1-cp39-abi3-win_amd64.whl", hash = "sha256:0f0dcbcc9f6e13e675a66d7a5f2f225a736745ce484c1a4e07476a89ccdad382"},
+    {file = "tokenizers-0.21.1.tar.gz", hash = "sha256:a1bb04dc5b448985f86ecd4b05407f5a8d97cb2c0532199b2a302a604a0165ab"},
 ]
 
 [package.dependencies]
@@ -5362,6 +5985,23 @@ build = ["cmake (>=3.20)", "lit"]
 tests = ["autopep8", "flake8", "isort", "llnl-hatchet", "numpy", "pytest", "scipy (>=1.7.1)"]
 tutorials = ["matplotlib", "pandas", "tabulate"]
 
+[[package]]
+name = "typer"
+version = "0.15.2"
+description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "typer-0.15.2-py3-none-any.whl", hash = "sha256:46a499c6107d645a9c13f7ee46c5d5096cae6f5fc57dd11eccbbb9ae3e44ddfc"},
+    {file = "typer-0.15.2.tar.gz", hash = "sha256:ab2fab47533a813c49fe1f16b1a370fd5819099c00b119e0633df65f22144ba5"},
+]
+
+[package.dependencies]
+click = ">=8.0.0"
+rich = ">=10.11.0"
+shellingham = ">=1.3.0"
+typing-extensions = ">=3.7.4.3"
+
 [[package]]
 name = "types-pyyaml"
 version = "6.0.12.20241230"
@@ -5499,6 +6139,42 @@ platformdirs = ">=3.9.1,<5"
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
+[[package]]
+name = "wasabi"
+version = "1.1.3"
+description = "A lightweight console printing and formatting toolkit"
+optional = true
+python-versions = ">=3.6"
+files = [
+    {file = "wasabi-1.1.3-py3-none-any.whl", hash = "sha256:f76e16e8f7e79f8c4c8be49b4024ac725713ab10cd7f19350ad18a8e3f71728c"},
+    {file = "wasabi-1.1.3.tar.gz", hash = "sha256:4bb3008f003809db0c3e28b4daf20906ea871a2bb43f9914197d540f4f2e0878"},
+]
+
+[package.dependencies]
+colorama = {version = ">=0.4.6", markers = "sys_platform == \"win32\" and python_version >= \"3.7\""}
+
+[[package]]
+name = "weasel"
+version = "0.4.1"
+description = "Weasel: A small and easy workflow system"
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "weasel-0.4.1-py3-none-any.whl", hash = "sha256:24140a090ea1ac512a2b2f479cc64192fd1d527a7f3627671268d08ed5ac418c"},
+    {file = "weasel-0.4.1.tar.gz", hash = "sha256:aabc210f072e13f6744e5c3a28037f93702433405cd35673f7c6279147085aa9"},
+]
+
+[package.dependencies]
+cloudpathlib = ">=0.7.0,<1.0.0"
+confection = ">=0.0.4,<0.2.0"
+packaging = ">=20.0"
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<3.0.0"
+requests = ">=2.13.0,<3.0.0"
+smart-open = ">=5.2.1,<8.0.0"
+srsly = ">=2.4.3,<3.0.0"
+typer = ">=0.3.0,<1.0.0"
+wasabi = ">=0.9.1,<1.2.0"
+
 [[package]]
 name = "weaviate-client"
 version = "4.11.1"
@@ -5856,6 +6532,7 @@ experimental = ["langchain-text-splitters", "llama-index", "pygraphviz", "pygrap
 google = ["google-cloud-aiplatform"]
 kg-creation-tools = ["pygraphviz", "pygraphviz"]
 mistralai = ["mistralai"]
+nlp = ["spacy"]
 ollama = ["ollama"]
 openai = ["openai"]
 pinecone = ["pinecone-client"]
@@ -5865,5 +6542,5 @@ weaviate = ["weaviate-client"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = "^3.9.0"
-content-hash = "6e3000c7eb7f83f5117ca2e6850bec628ed45fe0826f54fda703152c2f563911"
+python-versions = ">=3.9.0,<3.13"
+content-hash = "96275466c06e2d0bd89b102a8bb590f3c93caf1f5aa0fcd3ed2c0964df17496c"
diff --git a/pyproject.toml b/pyproject.toml
index 907d1c108..26f6213aa 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -28,7 +28,7 @@ include = "neo4j_graphrag"
 from = "src"
 
 [tool.poetry.dependencies]
-python = "^3.9.0"
+python = ">=3.9.0,<3.13"
 neo4j = "^5.17.0"
 pydantic = "^2.6.3"
 fsspec = "^2024.9.0"
@@ -53,6 +53,7 @@ openai = {version = "^1.51.1", optional = true }
 anthropic = {version = "^0.49.0", optional = true}
 sentence-transformers = {version = "^3.0.0", optional = true }
 ollama = {version = "^0.4.4", optional = true}
+spacy = { version = "3.8.3",  optional = true}
 
 [tool.poetry.group.dev.dependencies]
 urllib3 = "<2"
@@ -81,6 +82,7 @@ kg_creation_tools = ["pygraphviz"]
 sentence-transformers = ["sentence-transformers"]
 experimental = ["langchain-text-splitters", "pygraphviz", "llama-index"]
 examples = ["langchain-openai", "langchain-huggingface"]
+nlp = ["spacy"]
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
diff --git a/src/neo4j_graphrag/experimental/components/resolver.py b/src/neo4j_graphrag/experimental/components/resolver.py
index a050ea35e..fa1997657 100644
--- a/src/neo4j_graphrag/experimental/components/resolver.py
+++ b/src/neo4j_graphrag/experimental/components/resolver.py
@@ -13,14 +13,23 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 import abc
-from typing import Any, Optional
+import logging
+from itertools import combinations
+from typing import Any, Optional, List
 
 import neo4j
+import numpy as np
+from numpy.typing import NDArray
+import spacy
+from spacy.language import Language
+from spacy.cli.download import download as spacy_download
 
 from neo4j_graphrag.experimental.components.types import ResolutionStats
 from neo4j_graphrag.experimental.pipeline import Component
 from neo4j_graphrag.utils import driver_config
 
+logger = logging.getLogger(__name__)
+
 
 class EntityResolver(Component, abc.ABC):
     """Entity resolution base class
@@ -137,3 +146,181 @@ async def run(self) -> ResolutionStats:
             number_of_nodes_to_resolve=number_of_nodes_to_resolve,
             number_of_created_nodes=number_of_created_nodes,
         )
+
+
+class SpaCySemanticMatchResolver(EntityResolver):
+    """
+    Resolve entities with same label and similar set of textual properties (default is
+    ["name"]) based on spaCy's static embeddings and cosine similarities.
+
+    Args:
+        driver (neo4j.Driver): The Neo4j driver to connect to the database.
+        filter_query (Optional[str]): Optional Cypher WHERE clause to reduce the resolution scope.
+        resolve_properties (Optional[List[str]]): The list of properties to consider for embeddings Defaults to ["name"].
+        similarity_threshold (float): The similarity threshold above which nodes are merged. Defaults to 0.8.
+        spacy_model (str): The name of the spaCy model to load. Defaults to "en_core_web_lg".
+        neo4j_database (Optional[str]): The name of the Neo4j database. If not provided, this defaults to the server's default database ("neo4j" by default) (`see reference to documentation <https://neo4j.com/docs/operations-manual/current/database-administration/#manage-databases-default>`_).
+
+    Example:
+
+    .. code-block:: python
+
+        from neo4j import GraphDatabase
+        from neo4j_graphrag.experimental.components.resolver import SinglePropertyExactMatchResolver
+
+        URI = "neo4j://localhost:7687"
+        AUTH = ("neo4j", "password")
+        DATABASE = "neo4j"
+
+        driver = GraphDatabase.driver(URI, auth=AUTH)
+        resolver = SinglePropertyExactMatchResolver(driver=driver, neo4j_database=DATABASE)
+        await resolver.run()  # no expected parameters
+
+    """
+
+    def __init__(
+        self,
+        driver: neo4j.Driver,
+        filter_query: Optional[str] = None,
+        resolve_properties: Optional[List[str]] = None,
+        similarity_threshold: float = 0.8,
+        spacy_model: str = "en_core_web_lg",
+        neo4j_database: Optional[str] = None,
+    ) -> None:
+        super().__init__(driver, filter_query)
+        self.resolve_properties = resolve_properties or ["name"]
+        self.similarity_threshold = similarity_threshold
+        self.neo4j_database = neo4j_database
+        self.nlp = self._load_or_download_spacy_model(spacy_model)
+
+    async def run(self) -> ResolutionStats:
+        """Resolve entities based on the following rules:
+         For each entity label, entities with similar 'resolve_properties'
+        (cosine similarity on embedding vectors) are merged into a single node.
+
+        See apoc.refactor.mergeNodes documentation for more details.
+        """
+        match_query = "MATCH (entity:__Entity__)"
+        if self.filter_query:
+            match_query += f" {self.filter_query}"
+
+        # generate a dynamic map of requested properties, e.g. "name: entity.name, description: entity.description, ..."
+        props_map_list = [f"{prop}: entity.{prop}" for prop in self.resolve_properties]
+        props_map = ", ".join(props_map_list)
+
+        # Cypher query:
+        # matches extracted entities
+        # filters entities if filter_query is provided
+        # unwinds labels to skip reserved ones
+        # collects all properties needed for embeddings
+        query = f"""
+            {match_query}
+            UNWIND labels(entity) AS lab
+            WITH lab, entity
+            WHERE NOT lab IN ['__Entity__', '__KGBuilder__']
+            WITH lab, collect({{ id: id(entity), {props_map} }}) AS labelCluster
+            RETURN lab, labelCluster
+        """
+
+        records, _, _ = self.driver.execute_query(query, database_=self.neo4j_database)
+
+        total_entities_embedded = 0
+        total_merged_nodes = 0
+
+        # for each row, 'lab' is the label, 'labelCluster' is a list of dicts (id + textual properties)
+        for row in records:
+            entities = row["labelCluster"]
+
+            # build node embeddings
+            node_embeddings = {}
+            for ent in entities:
+                # concatenate all textual properties (if non-null) into a single string
+                texts = [
+                    str(ent[p]) for p in self.resolve_properties if p in ent and ent[p]
+                ]
+                combined_text = " ".join(texts).strip()
+                if combined_text:
+                    node_embeddings[ent["id"]] = self.nlp(combined_text).vector
+            total_entities_embedded += len(node_embeddings)
+
+            # identify pairs to merge
+            pairs_to_merge = []
+            for (id1, emb1), (id2, emb2) in combinations(node_embeddings.items(), 2):
+                sim = self._cosine_similarity(
+                    np.asarray(emb1, dtype=np.float64),
+                    np.asarray(emb2, dtype=np.float64),
+                )
+                if sim >= self.similarity_threshold:
+                    pairs_to_merge.append({id1, id2})
+
+            # consolidate overlapping sets of node IDs
+            resolved_sets = self._consolidate_sets(pairs_to_merge)
+
+            # perform merges in the db using APOC
+            merged_count = 0
+            for node_id_set in resolved_sets:
+                if len(node_id_set) > 1:
+                    merge_query = (
+                        "MATCH (n) WHERE id(n) IN $ids "
+                        "WITH collect(n) AS nodes "
+                        "CALL apoc.refactor.mergeNodes(nodes, {properties: 'discard', mergeRels: true}) "
+                        "YIELD node RETURN id(node)"
+                    )
+                    result, _, _ = self.driver.execute_query(
+                        merge_query,
+                        {"ids": list(node_id_set)},
+                        database_=self.neo4j_database,
+                    )
+                    merged_count += len(result)
+
+            total_merged_nodes += merged_count
+
+        return ResolutionStats(
+            number_of_nodes_to_resolve=total_entities_embedded,
+            number_of_created_nodes=total_merged_nodes,
+        )
+
+    @staticmethod
+    def _consolidate_sets(pairs: List[set[str]]) -> List[set[str]]:
+        """Consolidate overlapping sets of node pairs into unique sets."""
+        consolidated: List[set[str]] = []
+        for pair in pairs:
+            merged = False
+            for cons in consolidated:
+                # if there is any intersection, unify them
+                if pair & cons:
+                    cons.update(pair)
+                    merged = True
+                    break
+            if not merged:
+                consolidated.append(set(pair))
+        return consolidated
+
+    @staticmethod
+    def _cosine_similarity(
+        vec1: NDArray[np.float64], vec2: NDArray[np.float64]
+    ) -> float:
+        """Calculate cosine similarity between two embedding vectors."""
+        dot_product = np.dot(vec1, vec2)
+        norm1 = np.linalg.norm(vec1)
+        norm2 = np.linalg.norm(vec2)
+        if not norm1 or not norm2:
+            return 0.0
+        return float(dot_product / (norm1 * norm2))
+
+    @staticmethod
+    def _load_or_download_spacy_model(model_name: str) -> Language:
+        """
+        Attempt to load the specified spaCy model by name.
+        If not installed, automatically download and then load it.
+        """
+        try:
+            return spacy.load(model_name)
+        except OSError as e:
+            # handling cases where the spaCy model is not yet downloaded:
+            if "doesn't seem to be a Python package or a valid path" in str(e):
+                logger.info(f"Model '{model_name}' not found. Downloading...")
+                spacy_download(model_name)
+                return spacy.load(model_name)
+            else:
+                raise e
diff --git a/tests/unit/experimental/components/test_resolver.py b/tests/unit/experimental/components/test_resolver.py
index 558b23f5d..fded67d0e 100644
--- a/tests/unit/experimental/components/test_resolver.py
+++ b/tests/unit/experimental/components/test_resolver.py
@@ -18,6 +18,7 @@
 import pytest
 from neo4j_graphrag.experimental.components.resolver import (
     SinglePropertyExactMatchResolver,
+    SpaCySemanticMatchResolver,
 )
 from neo4j_graphrag.experimental.components.types import ResolutionStats
 
@@ -57,3 +58,105 @@ async def test_simple_resolver_custom_filter(driver: MagicMock) -> None:
             )
         ]
     )
+
+
+@pytest.mark.asyncio
+async def test_spacy_resolver_match_on_name_property(driver: MagicMock) -> None:
+    driver.execute_query.side_effect = [
+        (
+            [
+                neo4j.Record(
+                    {
+                        "lab": "Person",
+                        "labelCluster": [
+                            {"id": 1, "name": "Alice"},
+                            {"id": 2, "name": "Alice"},
+                        ],
+                    }
+                )
+            ],
+            None,
+            None,
+        ),
+        (
+            [neo4j.Record({"id(node)": 1})],
+            None,
+            None,
+        ),
+    ]
+
+    resolver = SpaCySemanticMatchResolver(driver=driver)
+
+    res = await resolver.run()
+    assert isinstance(res, ResolutionStats)
+    assert res.number_of_nodes_to_resolve == 2
+    assert res.number_of_created_nodes == 1
+
+    assert driver.execute_query.call_count == 2
+
+
+@pytest.mark.asyncio
+async def test_spacy_resolver_no_merge(driver: MagicMock) -> None:
+    driver.execute_query.side_effect = [
+        (
+            [
+                neo4j.Record(
+                    {
+                        "lab": "Person",
+                        "labelCluster": [
+                            {"id": 1, "name": "Alice"},
+                            {"id": 2, "name": "Bob"},
+                        ],
+                    }
+                )
+            ],
+            None,
+            None,
+        ),
+    ]
+
+    resolver = SpaCySemanticMatchResolver(driver=driver)
+
+    res = await resolver.run()
+    assert res.number_of_nodes_to_resolve == 2
+    assert res.number_of_created_nodes == 0
+
+    assert driver.execute_query.call_count == 1
+
+
+@pytest.mark.asyncio
+async def test_spacy_resolver_match_on_multiple_text_properties(
+    driver: MagicMock,
+) -> None:
+    driver.execute_query.side_effect = [
+        (
+            [
+                neo4j.Record(
+                    {
+                        "lab": "Person",
+                        "labelCluster": [
+                            {"id": 10, "name": "John Smith", "ssn": "23-45-6789"},
+                            {"id": 11, "name": "Jonathan Smith", "ssn": "23-45-6789"},
+                        ],
+                    }
+                )
+            ],
+            None,
+            None,
+        ),
+        (
+            [neo4j.Record({"id(node)": 10})],
+            None,
+            None,
+        ),
+    ]
+
+    resolver = SpaCySemanticMatchResolver(
+        driver=driver, resolve_properties=["name", "ssn"]
+    )
+    res = await resolver.run()
+    assert isinstance(res, ResolutionStats)
+    assert res.number_of_nodes_to_resolve == 2
+    assert res.number_of_created_nodes == 1
+
+    assert driver.execute_query.call_count == 2