diff --git a/CHANGELOG.md b/CHANGELOG.md
index 816f8a00..a248cb53 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,11 @@
 
 ### Changed
 - Updated LLM implementations to handle message history consistently across providers.
+- The `id_prefix` parameter in the `LexicalGraphConfig` is deprecated.
+
+### Fixed
+- IDs for the Document and Chunk nodes in the lexical graph are now randomly generated and unique across multiple runs, fixing issues in the lexical graph where relationships were created between chunks that were created by different pipeline runs.
+
 
 ## 1.3.0
 
diff --git a/docs/source/types.rst b/docs/source/types.rst
index adf3c9b6..34ef03b4 100644
--- a/docs/source/types.rst
+++ b/docs/source/types.rst
@@ -39,6 +39,12 @@ RagResultModel
 
 .. autoclass:: neo4j_graphrag.generation.types.RagResultModel
 
+DocumentInfo
+============
+
+.. autoclass:: neo4j_graphrag.experimental.components.types.DocumentInfo
+
+
 TextChunk
 =========
 
diff --git a/docs/source/user_guide_kg_builder.rst b/docs/source/user_guide_kg_builder.rst
index 87ce2f42..c4559072 100644
--- a/docs/source/user_guide_kg_builder.rst
+++ b/docs/source/user_guide_kg_builder.rst
@@ -672,7 +672,7 @@ Example usage:
     from neo4j_graphrag.experimental.pipeline.components.lexical_graph_builder import LexicalGraphBuilder
     from neo4j_graphrag.experimental.pipeline.components.types import LexicalGraphConfig
 
-    lexical_graph_builder = LexicalGraphBuilder(config=LexicalGraphConfig(id_prefix="example"))
+    lexical_graph_builder = LexicalGraphBuilder(config=LexicalGraphConfig())
     graph = await lexical_graph_builder.run(
         text_chunks=TextChunks(chunks=[
             TextChunk(text="some text", index=0),
@@ -713,7 +713,6 @@ Optionally, the document and chunk node labels can be configured using a `Lexica
     # optionally, define a LexicalGraphConfig object
     # shown below with the default values
     config = LexicalGraphConfig(
-        id_prefix="",  # used to prefix the chunk and document IDs
         chunk_node_label="Chunk",
         document_node_label="Document",
         chunk_to_document_relationship_type="PART_OF_DOCUMENT",
@@ -998,7 +997,7 @@ 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 single resolver that merges nodes
+In practice, this package implements a simple resolver that merges nodes
 with the same label and identical "name" property.
 
 .. warning::
@@ -1018,15 +1017,30 @@ It can be used like this:
 
 .. warning::
 
-    By default, all nodes with the __Entity__ label will be resolved.
-    To exclude specific nodes, a filter_query can be added to the query.
-    For example, if a `:Resolved` label has been applied to already resolved entities
-    in the graph, these entities can be excluded with the following approach:
+    By default, all nodes with the `__Entity__` label will be resolved.
+    This behavior can be controled using the `filter_query` parameter described below.
 
-    .. code:: python
+Filter Query Parameter
+----------------------
 
-        from neo4j_graphrag.experimental.components.resolver import (
-            SinglePropertyExactMatchResolver,
-        )
-        resolver = SinglePropertyExactMatchResolver(driver, filter_query="WHERE not entity:Resolved")
-        res = await resolver.run()
+To exclude specific nodes from the resolution, a `filter_query` can be added to the query.
+For example, if a `:Resolved` label has been applied to already resolved entities
+in the graph, these entities can be excluded with the following approach:
+
+.. code:: python
+
+    from neo4j_graphrag.experimental.components.resolver import (
+        SinglePropertyExactMatchResolver,
+    )
+    filter_query = "WHERE NOT entity:Resolved"
+    resolver = SinglePropertyExactMatchResolver(driver, filter_query=filter_query)
+    res = await resolver.run()
+
+
+Similar approach can be used to exclude entities created from a previous pipeline
+run on the same document, assuming a label `OldDocument` has been assigned to the
+previously created document node:
+
+.. code:: python
+
+    filter_query = "WHERE NOT EXISTS((entity)-[:FROM_DOCUMENT]->(:OldDocument))"
diff --git a/examples/build_graph/simple_kg_builder_from_pdf.py b/examples/build_graph/simple_kg_builder_from_pdf.py
index fd79a1d6..05ac6989 100644
--- a/examples/build_graph/simple_kg_builder_from_pdf.py
+++ b/examples/build_graph/simple_kg_builder_from_pdf.py
@@ -23,7 +23,7 @@
 DATABASE = "neo4j"
 
 
-root_dir = Path(__file__).parents[4]
+root_dir = Path(__file__).parents[1]
 file_path = root_dir / "data" / "Harry Potter and the Chamber of Secrets Summary.pdf"
 
 
diff --git a/examples/customize/build_graph/components/extractors/custom_extractor.py b/examples/customize/build_graph/components/extractors/custom_extractor.py
index 6c208086..dcc73d89 100644
--- a/examples/customize/build_graph/components/extractors/custom_extractor.py
+++ b/examples/customize/build_graph/components/extractors/custom_extractor.py
@@ -4,8 +4,8 @@
     EntityRelationExtractor,
     OnError,
 )
-from neo4j_graphrag.experimental.components.pdf_loader import DocumentInfo
 from neo4j_graphrag.experimental.components.types import (
+    DocumentInfo,
     LexicalGraphConfig,
     Neo4jGraph,
     TextChunks,
diff --git a/examples/customize/build_graph/components/lexical_graph_builder/lexical_graph_builder.py b/examples/customize/build_graph/components/lexical_graph_builder/lexical_graph_builder.py
index fd7feab7..63c5846d 100644
--- a/examples/customize/build_graph/components/lexical_graph_builder/lexical_graph_builder.py
+++ b/examples/customize/build_graph/components/lexical_graph_builder/lexical_graph_builder.py
@@ -13,7 +13,6 @@ async def main() -> GraphResult:
     # optionally, define a LexicalGraphConfig object
     # shown below with default values
     config = LexicalGraphConfig(
-        id_prefix="",  # used to prefix the chunk and document IDs
         chunk_node_label="Chunk",
         document_node_label="Document",
         chunk_to_document_relationship_type="PART_OF_DOCUMENT",
diff --git a/examples/customize/build_graph/components/loaders/custom_loader.py b/examples/customize/build_graph/components/loaders/custom_loader.py
index 35ebfd10..a8ca8142 100644
--- a/examples/customize/build_graph/components/loaders/custom_loader.py
+++ b/examples/customize/build_graph/components/loaders/custom_loader.py
@@ -3,11 +3,8 @@
 from pathlib import Path
 from typing import Dict, Optional
 
-from neo4j_graphrag.experimental.components.pdf_loader import (
-    DataLoader,
-    DocumentInfo,
-    PdfDocument,
-)
+from neo4j_graphrag.experimental.components.pdf_loader import DataLoader
+from neo4j_graphrag.experimental.components.types import DocumentInfo, PdfDocument
 
 
 class MyLoader(DataLoader):
diff --git a/examples/customize/build_graph/pipeline/lexical_graph_builder_from_text.py b/examples/customize/build_graph/pipeline/lexical_graph_builder_from_text.py
index b862dcc4..4c332802 100644
--- a/examples/customize/build_graph/pipeline/lexical_graph_builder_from_text.py
+++ b/examples/customize/build_graph/pipeline/lexical_graph_builder_from_text.py
@@ -33,7 +33,6 @@ async def main(neo4j_driver: neo4j.Driver) -> PipelineResult:
     pipe.add_component(TextChunkEmbedder(embedder=OpenAIEmbeddings()), "chunk_embedder")
     # optional: define some custom node labels for the lexical graph:
     lexical_graph_config = LexicalGraphConfig(
-        id_prefix="example",
         chunk_node_label="TextPart",
     )
     pipe.add_component(
diff --git a/examples/customize/build_graph/pipeline/text_to_lexical_graph_to_entity_graph_single_pipeline.py b/examples/customize/build_graph/pipeline/text_to_lexical_graph_to_entity_graph_single_pipeline.py
index c0cb5a5e..b7ba60e1 100644
--- a/examples/customize/build_graph/pipeline/text_to_lexical_graph_to_entity_graph_single_pipeline.py
+++ b/examples/customize/build_graph/pipeline/text_to_lexical_graph_to_entity_graph_single_pipeline.py
@@ -164,7 +164,6 @@ async def define_and_run_pipeline(
 async def main(driver: neo4j.Driver) -> PipelineResult:
     # optional: define some custom node labels for the lexical graph:
     lexical_graph_config = LexicalGraphConfig(
-        id_prefix="example",
         chunk_node_label="TextPart",
         document_node_label="Text",
     )
diff --git a/examples/customize/build_graph/pipeline/text_to_lexical_graph_to_entity_graph_two_pipelines.py b/examples/customize/build_graph/pipeline/text_to_lexical_graph_to_entity_graph_two_pipelines.py
index dcb720d8..7cfa4cbb 100644
--- a/examples/customize/build_graph/pipeline/text_to_lexical_graph_to_entity_graph_two_pipelines.py
+++ b/examples/customize/build_graph/pipeline/text_to_lexical_graph_to_entity_graph_two_pipelines.py
@@ -184,7 +184,6 @@ async def read_chunk_and_perform_entity_extraction(
 async def main(driver: neo4j.Driver) -> PipelineResult:
     # optional: define some custom node labels for the lexical graph:
     lexical_graph_config = LexicalGraphConfig(
-        id_prefix="example",
         document_node_label="Book",  # default: "Document"
         chunk_node_label="Chapter",  # default "Chunk"
         chunk_text_property="content",  # default: "text"
diff --git a/poetry.lock b/poetry.lock
index 21f8bf66..7221efad 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -13,87 +13,87 @@ files = [
 
 [[package]]
 name = "aiohttp"
-version = "3.11.10"
+version = "3.11.11"
 description = "Async http client/server framework (asyncio)"
 optional = true
 python-versions = ">=3.9"
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@@ -111,13 +111,13 @@ speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
 
 [[package]]
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-version = "1.3.1"
+version = "1.3.2"
 description = "aiosignal: a list of registered asynchronous callbacks"
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-python-versions = ">=3.7"
+python-versions = ">=3.9"
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@@ -205,19 +205,19 @@ files = [
 
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-version = "24.2.0"
+version = "24.3.0"
 description = "Classes Without Boilerplate"
 optional = true
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+dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
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 tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
@@ -284,13 +284,13 @@ files = [
 
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+version = "2024.12.14"
 description = "Python package for providing Mozilla's CA Bundle."
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 python-versions = ">=3.6"
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 ]
 
 [[package]]
 name = "click"
-version = "8.1.7"
+version = "8.1.8"
 description = "Composable command line interface toolkit"
 optional = true
 python-versions = ">=3.7"
 files = [
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 [package.dependencies]
@@ -513,20 +500,19 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [[package]]
 name = "cohere"
-version = "5.13.3"
+version = "5.13.4"
 description = ""
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
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 [package.dependencies]
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 httpx = ">=0.21.2"
 httpx-sse = "0.4.0"
-numpy = ">=1.26,<2.0"
 parameterized = ">=0.9.0,<0.10.0"
 pydantic = ">=1.9.2"
 pydantic-core = ">=2.18.2,<3.0.0"
@@ -535,9 +521,6 @@ tokenizers = ">=0.15,<1"
 types-requests = ">=2.0.0,<3.0.0"
 typing_extensions = ">=4.0.0"
 
-[package.extras]
-aws = ["boto3 (>=1.34.0,<2.0.0)", "sagemaker (>=2.232.1,<3.0.0)"]
-
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -551,73 +534,73 @@ files = [
 
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+version = "7.6.10"
 description = "Code coverage measurement for Python"
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 python-versions = ">=3.9"
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 [package.extras]
@@ -761,13 +744,13 @@ files = [
 
 [[package]]
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 description = "Like `typing._eval_type`, but lets older Python versions use newer typing features."
 optional = true
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 [package.extras]
@@ -952,13 +935,13 @@ files = [
 
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 tokenization = ["sentencepiece (>=0.2.0)"]
 vizier = ["google-vizier (>=0.1.6)"]
 xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
@@ -1146,13 +1129,13 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)", "grpcio-status (>=1.38.0,<2.0.dev0)"]
 
 [[package]]
 name = "google-cloud-resource-manager"
-version = "1.13.1"
+version = "1.14.0"
 description = "Google Cloud Resource Manager API client library"
 optional = true
 python-versions = ">=3.7"
 files = [
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-    {file = "google_cloud_resource_manager-1.13.1.tar.gz", hash = "sha256:bee9f2fb1d856731182b7cc05980d216aae848947ccdadf2848a2c64ccd6bbea"},
+    {file = "google_cloud_resource_manager-1.14.0-py2.py3-none-any.whl", hash = "sha256:4860c3ea9ace760b317ea90d4e27f1b32e54ededdcc340a7cb70c8ef238d8f7c"},
+    {file = "google_cloud_resource_manager-1.14.0.tar.gz", hash = "sha256:daa70a3a4704759d31f812ed221e3b6f7b660af30c7862e4a0060ea91291db30"},
 ]
 
 [package.dependencies]
@@ -1629,13 +1612,13 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "0.26.5"
+version = "0.27.0"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = true
 python-versions = ">=3.8.0"
 files = [
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+    {file = "huggingface_hub-0.27.0-py3-none-any.whl", hash = "sha256:8f2e834517f1f1ddf1ecc716f91b120d7333011b7485f665a9a412eacb1a2a81"},
+    {file = "huggingface_hub-0.27.0.tar.gz", hash = "sha256:902cce1a1be5739f5589e560198a65a8edcfd3b830b1666f36e4b961f0454fac"},
 ]
 
 [package.dependencies]
@@ -1674,13 +1657,13 @@ files = [
 
 [[package]]
 name = "identify"
-version = "2.6.3"
+version = "2.6.4"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.extras]
@@ -1747,13 +1730,13 @@ files = [
 
 [[package]]
 name = "jinja2"
-version = "3.1.4"
+version = "3.1.5"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1907,13 +1890,13 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.24"
+version = "0.3.28"
 description = "Building applications with LLMs through composability"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_core-0.3.24-py3-none-any.whl", hash = "sha256:97192552ef882a3dd6ae3b870a180a743801d0137a1159173f51ac555eeb7eec"},
-    {file = "langchain_core-0.3.24.tar.gz", hash = "sha256:460851e8145327f70b70aad7dce2cdbd285e144d14af82b677256b941fc99656"},
+    {file = "langchain_core-0.3.28-py3-none-any.whl", hash = "sha256:a02f81ca53a8eed757133797e5a602ca80c1324bbecb0c5d86ef7bd3d6625372"},
+    {file = "langchain_core-0.3.28.tar.gz", hash = "sha256:407f7607e6b3c0ebfd6094da95d39b701e22e59966698ef126799782953e7f2c"},
 ]
 
 [package.dependencies]
@@ -1948,43 +1931,43 @@ transformers = ">=4.39.0"
 
 [[package]]
 name = "langchain-openai"
-version = "0.2.12"
+version = "0.2.14"
 description = "An integration package connecting OpenAI and LangChain"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
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+    {file = "langchain_openai-0.2.14-py3-none-any.whl", hash = "sha256:d232496662f79ece9a11caf7d798ba863e559c771bc366814f7688e0fe664fe8"},
+    {file = "langchain_openai-0.2.14.tar.gz", hash = "sha256:7a514f309e356b182a337c0ed36ab3fbe34d9834a235a3b85cb7f91ae775d978"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.21,<0.4.0"
-openai = ">=1.55.3,<2.0.0"
+langchain-core = ">=0.3.27,<0.4.0"
+openai = ">=1.58.1,<2.0.0"
 tiktoken = ">=0.7,<1"
 
 [[package]]
 name = "langchain-text-splitters"
-version = "0.3.2"
+version = "0.3.4"
 description = "LangChain text splitting utilities"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.15,<0.4.0"
+langchain-core = ">=0.3.26,<0.4.0"
 
 [[package]]
 name = "langsmith"
-version = "0.2.3"
+version = "0.2.6"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -1998,20 +1981,22 @@ requests = ">=2,<3"
 requests-toolbelt = ">=1.0.0,<2.0.0"
 
 [package.extras]
+compression = ["zstandard (>=0.23.0,<0.24.0)"]
 langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"]
 
 [[package]]
 name = "llama-cloud"
-version = "0.1.6"
+version = "0.1.7"
 description = ""
 optional = true
 python-versions = "<4,>=3.8"
 files = [
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 ]
 
 [package.dependencies]
+certifi = ">=2024.7.4,<2025.0.0"
 httpx = ">=0.20.0"
 pydantic = ">=1.10"
 
@@ -2358,13 +2343,13 @@ files = [
 
 [[package]]
 name = "marshmallow"
-version = "3.23.1"
+version = "3.23.2"
 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
 optional = true
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -2520,49 +2505,49 @@ typing-extensions = {version = ">=4.1.0", markers = "python_version < \"3.11\""}
 
 [[package]]
 name = "mypy"
-version = "1.13.0"
+version = "1.14.0"
 description = "Optional static typing for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3815,10 +3801,7 @@ files = [
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 grpcio-tools = ">=1.41.0"
 httpx = {version = ">=0.20.0", extras = ["http2"]}
-numpy = [
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-    {version = ">=1.21", markers = "python_version >= \"3.8\" and python_version < \"3.12\""},
-]
+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"
@@ -3827,6 +3810,34 @@ urllib3 = ">=1.26.14,<3"
 fastembed = ["fastembed (==0.3.6)"]
 fastembed-gpu = ["fastembed-gpu (==0.3.6)"]
 
+[[package]]
+name = "qdrant-client"
+version = "1.12.2"
+description = "Client library for the Qdrant vector search engine"
+optional = true
+python-versions = ">=3.9"
+files = [
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+]
+
+[package.dependencies]
+grpcio = ">=1.41.0"
+grpcio-tools = ">=1.41.0"
+httpx = {version = ">=0.20.0", extras = ["http2"]}
+numpy = [
+    {version = ">=1.21", markers = "python_version >= \"3.10\" and python_version < \"3.12\""},
+    {version = ">=1.26", markers = "python_version >= \"3.12\" and python_version < \"3.13\""},
+    {version = ">=1.21,<2.1.0", markers = "python_version < \"3.10\""},
+]
+portalocker = ">=2.7.0,<3.0.0"
+pydantic = ">=1.10.8"
+urllib3 = ">=1.26.14,<3"
+
+[package.extras]
+fastembed = ["fastembed (==0.5.0)"]
+fastembed-gpu = ["fastembed-gpu (==0.5.0)"]
+
 [[package]]
 name = "regex"
 version = "2024.11.6"
@@ -4856,13 +4867,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "transformers"
-version = "4.47.0"
+version = "4.47.1"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = true
 python-versions = ">=3.9.0"
 files = [
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+    {file = "transformers-4.47.1.tar.gz", hash = "sha256:6c29c05a5f595e278481166539202bf8641281536df1c42357ee58a45d0a564a"},
 ]
 
 [package.dependencies]
@@ -4947,13 +4958,13 @@ tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "types-pyyaml"
-version = "6.0.12.20240917"
+version = "6.0.12.20241230"
 description = "Typing stubs for PyYAML"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -5034,6 +5045,16 @@ brotli = ["brotli (==1.0.9)", "brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotl
 secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
 socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
+[[package]]
+name = "uuid"
+version = "1.30"
+description = "UUID object and generation functions (Python 2.3 or higher)"
+optional = false
+python-versions = "*"
+files = [
+    {file = "uuid-1.30.tar.gz", hash = "sha256:1f87cc004ac5120466f36c5beae48b4c48cc411968eed0eaecd3da82aa96193f"},
+]
+
 [[package]]
 name = "validators"
 version = "0.34.0"
@@ -5068,15 +5089,26 @@ 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 = "weaviate"
+version = "0.1.2"
+description = "A placeholder package for the Weaviate name"
+optional = false
+python-versions = "*"
+files = [
+    {file = "weaviate-0.1.2-py3-none-any.whl", hash = "sha256:40f1c1cf0b769036315d2b6026c8cd823a3a6e951c90d4e70a001a770ba8a444"},
+    {file = "weaviate-0.1.2.tar.gz", hash = "sha256:a381b8bb0eb236bd10256def8612953ed9024e6738b8a259e7ec11e626ae0665"},
+]
+
 [[package]]
 name = "weaviate-client"
-version = "4.10.1"
+version = "4.10.2"
 description = "A python native Weaviate client"
 optional = true
 python-versions = ">=3.9"
 files = [
-    {file = "weaviate_client-4.10.1-py3-none-any.whl", hash = "sha256:eedd693b2bbd02279109f9a37d2c33492bb460e480f4c5a4297530d4ad78469e"},
-    {file = "weaviate_client-4.10.1.tar.gz", hash = "sha256:7a1513d0ce7d918100d255224da52fcfe3d0834a2d22069853ab95a2a17f102c"},
+    {file = "weaviate_client-4.10.2-py3-none-any.whl", hash = "sha256:e1706438aa7b57be5443bbdebff206cc6688110d1669d54c2721b3aa640b2c4c"},
+    {file = "weaviate_client-4.10.2.tar.gz", hash = "sha256:fde5ad8e36604674d26b115288b58a7e182c91e36c2b41a00d18a36fe4ec7e3f"},
 ]
 
 [package.dependencies]
@@ -5295,4 +5327,4 @@ weaviate = ["weaviate-client"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9.0"
-content-hash = "c2ab4d7e2b6f8dfa668cdab458068d085425115cbb08c201d3eb3be32c47325b"
+content-hash = "b05fbd4ce521d080d3dc2b7d2fa6a8e66cdc88b60f635b627aa7e7cd81ea65d4"
diff --git a/pyproject.toml b/pyproject.toml
index 018fa586..9b9c6415 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -51,6 +51,8 @@ sentence-transformers = {version = "^3.0.0", optional = true }
 json-repair = "^0.30.2"
 types-pyyaml = "^6.0.12.20240917"
 ollama = {version = "^0.4.4", optional = true}
+uuid = "^1.30"
+weaviate = "^0.1.2"
 
 [tool.poetry.group.dev.dependencies]
 urllib3 = "<2"
diff --git a/src/neo4j_graphrag/experimental/components/embedder.py b/src/neo4j_graphrag/experimental/components/embedder.py
index adf9c46a..f113ecde 100644
--- a/src/neo4j_graphrag/experimental/components/embedder.py
+++ b/src/neo4j_graphrag/experimental/components/embedder.py
@@ -57,7 +57,10 @@ def _embed_chunk(self, text_chunk: TextChunk) -> TextChunk:
         metadata = text_chunk.metadata if text_chunk.metadata else {}
         metadata["embedding"] = embedding
         return TextChunk(
-            text=text_chunk.text, index=text_chunk.index, metadata=metadata
+            text=text_chunk.text,
+            index=text_chunk.index,
+            metadata=metadata,
+            uid=text_chunk.uid,
         )
 
     @validate_call
diff --git a/src/neo4j_graphrag/experimental/components/entity_relation_extractor.py b/src/neo4j_graphrag/experimental/components/entity_relation_extractor.py
index d4070aea..c1f7a610 100644
--- a/src/neo4j_graphrag/experimental/components/entity_relation_extractor.py
+++ b/src/neo4j_graphrag/experimental/components/entity_relation_extractor.py
@@ -19,7 +19,6 @@
 import enum
 import json
 import logging
-from datetime import datetime
 from typing import Any, List, Optional, Union, cast
 
 import json_repair
@@ -27,9 +26,9 @@
 
 from neo4j_graphrag.exceptions import LLMGenerationError
 from neo4j_graphrag.experimental.components.lexical_graph import LexicalGraphBuilder
-from neo4j_graphrag.experimental.components.pdf_loader import DocumentInfo
 from neo4j_graphrag.experimental.components.schema import SchemaConfig
 from neo4j_graphrag.experimental.components.types import (
+    DocumentInfo,
     LexicalGraphConfig,
     Neo4jGraph,
     TextChunk,
@@ -141,17 +140,19 @@ async def run(
         pass
 
     def update_ids(
-        self, graph: Neo4jGraph, chunk_index: int, run_id: str
+        self,
+        graph: Neo4jGraph,
+        chunk: TextChunk,
     ) -> Neo4jGraph:
-        """Make node IDs unique across chunks and pipeline runs by
-        prefixing them with a custom prefix (set in the run method)
-        and chunk index."""
-        prefix = f"{run_id}:{chunk_index}"
+        """Make node IDs unique across chunks, document and pipeline runs
+        by prefixing them with a unique prefix.
+        """
+        prefix = f"{chunk.chunk_id}"
         for node in graph.nodes:
             node.id = f"{prefix}:{node.id}"
             if node.properties is None:
                 node.properties = {}
-            node.properties.update({"chunk_index": chunk_index})
+            node.properties.update({"chunk_index": chunk.index})
         for rel in graph.relationships:
             rel.start_node_id = f"{prefix}:{rel.start_node_id}"
             rel.end_node_id = f"{prefix}:{rel.end_node_id}"
@@ -241,14 +242,13 @@ async def post_process_chunk(
         self,
         chunk_graph: Neo4jGraph,
         chunk: TextChunk,
-        run_id: str,
         lexical_graph_builder: Optional[LexicalGraphBuilder] = None,
     ) -> None:
         """Perform post-processing after entity and relation extraction:
         - Update node IDs to make them unique across chunks
         - Build the lexical graph if requested
         """
-        self.update_ids(chunk_graph, chunk.index, run_id)
+        self.update_ids(chunk_graph, chunk)
         if lexical_graph_builder:
             await lexical_graph_builder.process_chunk_extracted_entities(
                 chunk_graph,
@@ -271,7 +271,6 @@ def combine_chunk_graphs(
     async def run_for_chunk(
         self,
         sem: asyncio.Semaphore,
-        run_id: str,
         chunk: TextChunk,
         schema: SchemaConfig,
         examples: str,
@@ -283,7 +282,6 @@ async def run_for_chunk(
             await self.post_process_chunk(
                 chunk_graph,
                 chunk,
-                run_id,
                 lexical_graph_builder,
             )
             return chunk_graph
@@ -312,7 +310,6 @@ async def run(
             schema (SchemaConfig | None): Definition of the schema to guide the LLM in its extraction. Caution: at the moment, there is no guarantee that the extracted entities and relations will strictly obey the schema.
             examples (str): Examples for few-shot learning in the prompt.
         """
-        run_id = str(int(datetime.now().timestamp()))
         lexical_graph_builder = None
         lexical_graph = None
         if self.create_lexical_graph:
@@ -330,7 +327,6 @@ async def run(
         tasks = [
             self.run_for_chunk(
                 sem,
-                run_id,
                 chunk,
                 schema,
                 examples,
diff --git a/src/neo4j_graphrag/experimental/components/lexical_graph.py b/src/neo4j_graphrag/experimental/components/lexical_graph.py
index ce96b9fd..bbe99b80 100644
--- a/src/neo4j_graphrag/experimental/components/lexical_graph.py
+++ b/src/neo4j_graphrag/experimental/components/lexical_graph.py
@@ -13,13 +13,15 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 import asyncio
+import datetime
 import logging
+from itertools import zip_longest
 from typing import Any, Dict, Optional
 
 from pydantic import validate_call
 
-from neo4j_graphrag.experimental.components.pdf_loader import DocumentInfo
 from neo4j_graphrag.experimental.components.types import (
+    DocumentInfo,
     GraphResult,
     LexicalGraphConfig,
     Neo4jGraph,
@@ -61,41 +63,43 @@ async def run(
                 "because no document metadata is provided"
             )
         graph = Neo4jGraph()
-        document_id = None
         if document_info:
             document_node = self.create_document_node(document_info)
             graph.nodes.append(document_node)
-            document_id = document_node.id
-        tasks = [
-            self.process_chunk(graph, chunk, document_id)
-            for chunk in text_chunks.chunks
-        ]
-        await asyncio.gather(*tasks)
+        if len(text_chunks.chunks) > 0:
+            tasks = [
+                self.process_chunk(graph, chunk, next_chunk, document_info)
+                for chunk, next_chunk in zip_longest(
+                    text_chunks.chunks, text_chunks.chunks[1:]
+                )
+            ]
+            await asyncio.gather(*tasks)
         return GraphResult(
             config=self.config,
             graph=graph,
         )
 
-    def chunk_id(self, chunk_index: int) -> str:
-        return f"{self.config.id_prefix}:{chunk_index}"
-
     async def process_chunk(
         self,
         graph: Neo4jGraph,
         chunk: TextChunk,
-        document_id: Optional[str] = None,
+        next_chunk: Optional[TextChunk],
+        document_info: Optional[DocumentInfo] = None,
     ) -> None:
         """Add chunks and relationships between them (NEXT_CHUNK)
 
         Updates `graph` in place.
         """
-        if document_id:
-            chunk_to_doc_rel = self.create_chunk_to_document_rel(chunk, document_id)
-            graph.relationships.append(chunk_to_doc_rel)
         chunk_node = self.create_chunk_node(chunk)
         graph.nodes.append(chunk_node)
-        if chunk.index > 0:
-            next_chunk_rel = self.create_next_chunk_relationship(chunk)
+        if document_info:
+            chunk_to_doc_rel = self.create_chunk_to_document_rel(
+                chunk,
+                document_info,
+            )
+            graph.relationships.append(chunk_to_doc_rel)
+        if next_chunk:
+            next_chunk_rel = self.create_next_chunk_relationship(chunk, next_chunk)
             graph.relationships.append(next_chunk_rel)
 
     def create_document_node(self, document_info: DocumentInfo) -> Neo4jNode:
@@ -104,19 +108,23 @@ def create_document_node(self, document_info: DocumentInfo) -> Neo4jNode:
         """
         document_metadata = document_info.metadata or {}
         return Neo4jNode(
-            id=document_info.path,
+            id=document_info.document_id,
             label=self.config.document_node_label,
             properties={
                 "path": document_info.path,
+                "createdAt": datetime.datetime.now(datetime.timezone.utc).isoformat(),
                 **document_metadata,
             },
         )
 
-    def create_chunk_node(self, chunk: TextChunk) -> Neo4jNode:
+    def create_chunk_node(
+        self,
+        chunk: TextChunk,
+    ) -> Neo4jNode:
         """Create chunk node with properties 'text', 'index' and any 'metadata'
         added during the process. Special case for the potential chunk embedding
         property that gets added as an embedding_property"""
-        chunk_id = self.chunk_id(chunk.index)
+        chunk_id = chunk.chunk_id
         chunk_properties: Dict[str, Any] = {
             self.config.chunk_text_property: chunk.text,
             self.config.chunk_index_property: chunk.index,
@@ -136,27 +144,27 @@ def create_chunk_node(self, chunk: TextChunk) -> Neo4jNode:
         )
 
     def create_chunk_to_document_rel(
-        self, chunk: TextChunk, document_id: str
+        self,
+        chunk: TextChunk,
+        document_info: DocumentInfo,
     ) -> Neo4jRelationship:
         """Create the relationship between a chunk and the document it belongs to."""
-        chunk_id = self.chunk_id(chunk.index)
         return Neo4jRelationship(
-            start_node_id=chunk_id,
-            end_node_id=document_id,
+            start_node_id=chunk.chunk_id,
+            end_node_id=document_info.document_id,
             type=self.config.chunk_to_document_relationship_type,
         )
 
     def create_next_chunk_relationship(
         self,
         chunk: TextChunk,
+        next_chunk: TextChunk,
     ) -> Neo4jRelationship:
         """Create relationship between a chunk and the next one"""
-        chunk_id = self.chunk_id(chunk.index)
-        previous_chunk_id = self.chunk_id(chunk.index - 1)
         return Neo4jRelationship(
             type=self.config.next_chunk_relationship_type,
-            start_node_id=previous_chunk_id,
-            end_node_id=chunk_id,
+            start_node_id=chunk.chunk_id,
+            end_node_id=next_chunk.chunk_id,
         )
 
     def create_node_to_chunk_rel(
@@ -185,9 +193,5 @@ async def process_chunk_extracted_entities(
                 self.config.document_node_label,
             ):
                 continue
-            if chunk.metadata and (id := chunk.metadata.get("id")):
-                chunk_id = id
-            else:
-                chunk_id = self.chunk_id(chunk.index)
-            node_to_chunk_rel = self.create_node_to_chunk_rel(node, chunk_id)
+            node_to_chunk_rel = self.create_node_to_chunk_rel(node, chunk.chunk_id)
             chunk_graph.relationships.append(node_to_chunk_rel)
diff --git a/src/neo4j_graphrag/experimental/components/neo4j_reader.py b/src/neo4j_graphrag/experimental/components/neo4j_reader.py
index 1cb6ff4a..352ed1a6 100644
--- a/src/neo4j_graphrag/experimental/components/neo4j_reader.py
+++ b/src/neo4j_graphrag/experimental/components/neo4j_reader.py
@@ -102,13 +102,14 @@ async def run(
         chunks = []
         for record in result:
             chunk = record.get("chunk")
-            text = chunk.pop(lexical_graph_config.chunk_text_property, "")
-            index = chunk.pop(lexical_graph_config.chunk_index_property, -1)
-            chunks.append(
-                TextChunk(
-                    text=text,
-                    index=index,
-                    metadata=chunk,
-                )
-            )
+            input_data = {
+                "text": chunk.pop(lexical_graph_config.chunk_text_property, ""),
+                "index": chunk.pop(lexical_graph_config.chunk_index_property, -1),
+            }
+            if (
+                uid := chunk.pop(lexical_graph_config.chunk_id_property, None)
+            ) is not None:
+                input_data["uid"] = uid
+            input_data["metadata"] = chunk
+            chunks.append(TextChunk(**input_data))
         return TextChunks(chunks=chunks)
diff --git a/src/neo4j_graphrag/experimental/components/pdf_loader.py b/src/neo4j_graphrag/experimental/components/pdf_loader.py
index c925c677..979cdb66 100644
--- a/src/neo4j_graphrag/experimental/components/pdf_loader.py
+++ b/src/neo4j_graphrag/experimental/components/pdf_loader.py
@@ -25,17 +25,8 @@
 from fsspec.implementations.local import LocalFileSystem
 
 from neo4j_graphrag.exceptions import PdfLoaderError
-from neo4j_graphrag.experimental.pipeline.component import Component, DataModel
-
-
-class DocumentInfo(DataModel):
-    path: str
-    metadata: Optional[Dict[str, str]] = None
-
-
-class PdfDocument(DataModel):
-    text: str
-    document_info: DocumentInfo
+from neo4j_graphrag.experimental.components.types import DocumentInfo, PdfDocument
+from neo4j_graphrag.experimental.pipeline.component import Component
 
 
 class DataLoader(Component):
diff --git a/src/neo4j_graphrag/experimental/components/types.py b/src/neo4j_graphrag/experimental/components/types.py
index 093bb26d..689e6b6c 100644
--- a/src/neo4j_graphrag/experimental/components/types.py
+++ b/src/neo4j_graphrag/experimental/components/types.py
@@ -14,25 +14,55 @@
 #  limitations under the License.
 from __future__ import annotations
 
-from typing import Any, Optional
+import uuid
+from typing import Any, Dict, Optional
 
-from pydantic import BaseModel, field_validator
+from pydantic import BaseModel, Field, field_validator
 
 from neo4j_graphrag.experimental.pipeline.component import DataModel
 
 
+class DocumentInfo(DataModel):
+    """A document loaded by a DataLoader.
+
+    Attributes:
+        path (str): Document path.
+        metadata (Optional[dict[str, Any]]): Metadata associated with this document.
+        uid (str): Unique identifier for this document.
+    """
+
+    path: str
+    metadata: Optional[Dict[str, str]] = None
+    uid: str = Field(default_factory=lambda: str(uuid.uuid4()))
+
+    @property
+    def document_id(self) -> str:
+        return self.uid
+
+
+class PdfDocument(DataModel):
+    text: str
+    document_info: DocumentInfo
+
+
 class TextChunk(BaseModel):
     """A chunk of text split from a document by a text splitter.
 
     Attributes:
         text (str): The raw chunk text.
         index (int): The position of this chunk in the original document.
-        metadata (Optional[dict[str, Any]]): Metadata associated with this chunk such as the id of the next chunk in the original document.
+        metadata (Optional[dict[str, Any]]): Metadata associated with this chunk.
+        uid (str): Unique identifier for this chunk.
     """
 
     text: str
     index: int
     metadata: Optional[dict[str, Any]] = None
+    uid: str = Field(default_factory=lambda: str(uuid.uuid4()))
+
+    @property
+    def chunk_id(self) -> str:
+        return self.uid
 
 
 class TextChunks(DataModel):
@@ -110,6 +140,7 @@ class ResolutionStats(DataModel):
 DEFAULT_CHUNK_TO_DOCUMENT_RELATIONSHIP_TYPE = "FROM_DOCUMENT"
 DEFAULT_NEXT_CHUNK_RELATIONSHIP_TYPE = "NEXT_CHUNK"
 DEFAULT_NODE_TO_CHUNK_RELATIONSHIP_TYPE = "FROM_CHUNK"
+DEFAULT_CHUNK_ID_PROPERTY = "id"
 DEFAULT_CHUNK_INDEX_PROPERTY = "index"
 DEFAULT_CHUNK_TEXT_PROPERTY = "text"
 DEFAULT_CHUNK_EMBEDDING_PROPERTY = "embedding"
@@ -118,7 +149,7 @@ class ResolutionStats(DataModel):
 class LexicalGraphConfig(BaseModel):
     """Configure all labels and property names in the lexical graph."""
 
-    id_prefix: str = ""
+    id_prefix: str = Field(deprecated=True, default="")
     document_node_label: str = DEFAULT_DOCUMENT_NODE_LABEL
     chunk_node_label: str = DEFAULT_CHUNK_NODE_LABEL
     chunk_to_document_relationship_type: str = (
@@ -126,6 +157,7 @@ class LexicalGraphConfig(BaseModel):
     )
     next_chunk_relationship_type: str = DEFAULT_NEXT_CHUNK_RELATIONSHIP_TYPE
     node_to_chunk_relationship_type: str = DEFAULT_NODE_TO_CHUNK_RELATIONSHIP_TYPE
+    chunk_id_property: str = DEFAULT_CHUNK_ID_PROPERTY
     chunk_index_property: str = DEFAULT_CHUNK_INDEX_PROPERTY
     chunk_text_property: str = DEFAULT_CHUNK_TEXT_PROPERTY
     chunk_embedding_property: str = DEFAULT_CHUNK_EMBEDDING_PROPERTY
diff --git a/src/neo4j_graphrag/llm/anthropic_llm.py b/src/neo4j_graphrag/llm/anthropic_llm.py
index 04d6555e..614c5b9c 100644
--- a/src/neo4j_graphrag/llm/anthropic_llm.py
+++ b/src/neo4j_graphrag/llm/anthropic_llm.py
@@ -13,7 +13,7 @@
 #  limitations under the License.
 from __future__ import annotations
 
-from typing import Any, Iterable, Optional, TYPE_CHECKING, cast
+from typing import TYPE_CHECKING, Any, Iterable, Optional, cast
 
 from pydantic import ValidationError
 
diff --git a/src/neo4j_graphrag/llm/cohere_llm.py b/src/neo4j_graphrag/llm/cohere_llm.py
index 63e54aaa..024d578a 100644
--- a/src/neo4j_graphrag/llm/cohere_llm.py
+++ b/src/neo4j_graphrag/llm/cohere_llm.py
@@ -15,6 +15,7 @@
 from __future__ import annotations
 
 from typing import TYPE_CHECKING, Any, Iterable, Optional, cast
+
 from pydantic import ValidationError
 
 from neo4j_graphrag.exceptions import LLMGenerationError
diff --git a/src/neo4j_graphrag/llm/mistralai_llm.py b/src/neo4j_graphrag/llm/mistralai_llm.py
index a3c84759..761b9a62 100644
--- a/src/neo4j_graphrag/llm/mistralai_llm.py
+++ b/src/neo4j_graphrag/llm/mistralai_llm.py
@@ -16,6 +16,7 @@
 
 import os
 from typing import Any, Iterable, Optional, cast
+
 from pydantic import ValidationError
 
 from neo4j_graphrag.exceptions import LLMGenerationError
@@ -30,7 +31,7 @@
 )
 
 try:
-    from mistralai import Mistral, Messages
+    from mistralai import Messages, Mistral
     from mistralai.models.sdkerror import SDKError
 except ImportError:
     Mistral = None  # type: ignore
diff --git a/src/neo4j_graphrag/llm/ollama_llm.py b/src/neo4j_graphrag/llm/ollama_llm.py
index a36d34f9..08dfa655 100644
--- a/src/neo4j_graphrag/llm/ollama_llm.py
+++ b/src/neo4j_graphrag/llm/ollama_llm.py
@@ -13,7 +13,8 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 from __future__ import annotations
-from typing import Any, Iterable, Optional, Sequence, TYPE_CHECKING, cast
+
+from typing import TYPE_CHECKING, Any, Iterable, Optional, Sequence, cast
 
 from pydantic import ValidationError
 
@@ -24,9 +25,9 @@
     BaseMessage,
     LLMMessage,
     LLMResponse,
+    MessageList,
     SystemMessage,
     UserMessage,
-    MessageList,
 )
 
 if TYPE_CHECKING:
diff --git a/src/neo4j_graphrag/llm/openai_llm.py b/src/neo4j_graphrag/llm/openai_llm.py
index b3d99411..353dd19d 100644
--- a/src/neo4j_graphrag/llm/openai_llm.py
+++ b/src/neo4j_graphrag/llm/openai_llm.py
@@ -25,9 +25,9 @@
     BaseMessage,
     LLMMessage,
     LLMResponse,
+    MessageList,
     SystemMessage,
     UserMessage,
-    MessageList,
 )
 
 if TYPE_CHECKING:
diff --git a/src/neo4j_graphrag/llm/types.py b/src/neo4j_graphrag/llm/types.py
index 77e89aef..2d293e93 100644
--- a/src/neo4j_graphrag/llm/types.py
+++ b/src/neo4j_graphrag/llm/types.py
@@ -1,6 +1,7 @@
-from pydantic import BaseModel
 from typing import Literal, TypedDict
 
+from pydantic import BaseModel
+
 
 class LLMResponse(BaseModel):
     content: str
diff --git a/src/neo4j_graphrag/llm/vertexai_llm.py b/src/neo4j_graphrag/llm/vertexai_llm.py
index 48acfc9f..f2cbe26a 100644
--- a/src/neo4j_graphrag/llm/vertexai_llm.py
+++ b/src/neo4j_graphrag/llm/vertexai_llm.py
@@ -23,10 +23,10 @@
 
 try:
     from vertexai.generative_models import (
+        Content,
         GenerativeModel,
-        ResponseValidationError,
         Part,
-        Content,
+        ResponseValidationError,
     )
 except ImportError:
     GenerativeModel = None
diff --git a/tests/e2e/experimental/pipeline/config/test_pipeline_runner_e2e.py b/tests/e2e/experimental/pipeline/config/test_pipeline_runner_e2e.py
index 9122a935..77f8cb8f 100644
--- a/tests/e2e/experimental/pipeline/config/test_pipeline_runner_e2e.py
+++ b/tests/e2e/experimental/pipeline/config/test_pipeline_runner_e2e.py
@@ -1,16 +1,30 @@
+#  Copyright (c) "Neo4j"
+#  Neo4j Sweden AB [https://neo4j.com]
+#  #
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#  #
+#      https://www.apache.org/licenses/LICENSE-2.0
+#  #
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
 import os
 from typing import Any
 from unittest.mock import AsyncMock, Mock, patch
 
-import neo4j
 import pytest
+from neo4j import Driver
 from neo4j_graphrag.experimental.pipeline.config.runner import PipelineRunner
 from neo4j_graphrag.experimental.pipeline.pipeline import PipelineResult
 from neo4j_graphrag.llm import LLMResponse
 
 
 @pytest.fixture(scope="function", autouse=True)
-def clear_db(driver: neo4j.Driver) -> Any:
+def clear_db(driver: Driver) -> Any:
     driver.execute_query("MATCH (n) DETACH DELETE n")
     yield
 
diff --git a/tests/e2e/test_lexical_graph_builder_component_e2e.py b/tests/e2e/test_lexical_graph_builder_component_e2e.py
index c27d120f..de083179 100644
--- a/tests/e2e/test_lexical_graph_builder_component_e2e.py
+++ b/tests/e2e/test_lexical_graph_builder_component_e2e.py
@@ -12,13 +12,8 @@
 #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
-from unittest.mock import MagicMock
-
 import neo4j
 import pytest
-from neo4j_graphrag.experimental.components.entity_relation_extractor import (
-    LLMEntityRelationExtractor,
-)
 from neo4j_graphrag.experimental.components.kg_writer import Neo4jWriter
 from neo4j_graphrag.experimental.components.lexical_graph import LexicalGraphBuilder
 from neo4j_graphrag.experimental.components.types import (
@@ -27,7 +22,6 @@
     TextChunks,
 )
 from neo4j_graphrag.experimental.pipeline import Pipeline
-from neo4j_graphrag.llm import LLMResponse
 
 
 @pytest.mark.asyncio
@@ -64,90 +58,3 @@ async def test_lexical_graph_component_alone_default_config(
     assert len(created_chunks.records) == 0
     created_rels = driver.execute_query("MATCH ()-[r]->() RETURN r")
     assert len(created_rels.records) == 0
-
-
-@pytest.mark.asyncio
-@pytest.mark.usefixtures("setup_neo4j_for_kg_construction")
-async def test_lexical_graph_before_extractor_custom_prefix(
-    driver: neo4j.Driver, llm: MagicMock
-) -> None:
-    driver.execute_query("MATCH (n) DETACH DELETE n")
-    llm.ainvoke.side_effect = [
-        LLMResponse(
-            content="""{
-                    "nodes": [
-                        {
-                            "id": "0",
-                            "label": "Person",
-                            "properties": {
-                                "name": "Harry Potter"
-                            }
-                        },
-                        {
-                            "id": "1",
-                            "label": "Person",
-                            "properties": {
-                                "name": "Alastor Mad-Eye Moody"
-                            }
-                        },
-                    ],
-                    "relationships": [
-                        {
-                            "type": "KNOWS",
-                            "start_node_id": "0",
-                            "end_node_id": "1"
-                        },
-                    ]
-                }"""
-        ),
-    ]
-    pipe = Pipeline()
-    pipe.add_component(
-        LexicalGraphBuilder(config=LexicalGraphConfig(id_prefix="myPrefix")),
-        "lexical_graph",
-    )
-    pipe.add_component(
-        LLMEntityRelationExtractor(llm, create_lexical_graph=False), "extractor"
-    )
-    pipe.add_component(Neo4jWriter(driver), "lg_writer")  # lexical graph writer
-    pipe.add_component(Neo4jWriter(driver), "eg_writer")  # entity graph writer
-    chunks = TextChunks(chunks=[TextChunk(text="my text", index=0)])
-    pipe.connect("lexical_graph", "lg_writer", {"graph": "lexical_graph.graph"})
-    pipe.connect(
-        "lexical_graph", "extractor", {"lexical_graph_config": "lexical_graph.config"}
-    )
-    pipe.connect("extractor", "eg_writer", {"graph": "extractor"})
-
-    result = await pipe.run(
-        {"lexical_graph": {"text_chunks": chunks}, "extractor": {"chunks": chunks}}
-    )
-    assert result.result == {
-        "eg_writer": {
-            "status": "SUCCESS",
-            "metadata": {"node_count": 2, "relationship_count": 3},
-        },
-        "lg_writer": {
-            "status": "SUCCESS",
-            "metadata": {"node_count": 1, "relationship_count": 0},
-        },
-    }
-
-    # check the lexical graph has been created
-    default_config = LexicalGraphConfig()
-    created_chunks = driver.execute_query(
-        f"MATCH (n:{default_config.chunk_node_label}) RETURN n"
-    )
-    assert len(created_chunks.records) == 1
-    created_documents = driver.execute_query(
-        f"MATCH (n:{default_config.document_node_label}) RETURN n"
-    )
-    assert len(created_documents.records) == 0
-
-    # check the entity graph has been created
-    created_persons = driver.execute_query("MATCH (n:Person) RETURN n")
-    assert len(created_persons.records) == 2
-
-    created_entity_to_chunk_rels = driver.execute_query(
-        f"MATCH ()-[r:{default_config.node_to_chunk_relationship_type}]->() RETURN r"
-    )
-    assert len(created_entity_to_chunk_rels.records) == 2
diff --git a/tests/e2e/test_neo4j_reader_component_e2e.py b/tests/e2e/test_neo4j_reader_component_e2e.py
index 8de9ec23..e33a5c0e 100644
--- a/tests/e2e/test_neo4j_reader_component_e2e.py
+++ b/tests/e2e/test_neo4j_reader_component_e2e.py
@@ -32,10 +32,16 @@ async def test_neo4j_reader(driver: neo4j.Driver) -> None:
     res = await reader.run()
     assert len(res.chunks) == 2
     assert res.chunks[0] == TextChunk(
-        index=0, text="some text", metadata={"id": "0", "embedding": None}
+        index=0,
+        text="some text",
+        metadata={"embedding": None},
+        uid="0",
     )
     assert res.chunks[1] == TextChunk(
-        index=1, text="some longer text", metadata={"id": "1", "embedding": None}
+        index=1,
+        text="some longer text",
+        metadata={"embedding": None},
+        uid="1",
     )
 
 
diff --git a/tests/e2e/test_simplekgpipeline_e2e.py b/tests/e2e/test_simplekgpipeline_e2e.py
index 4d3059c7..25f61721 100644
--- a/tests/e2e/test_simplekgpipeline_e2e.py
+++ b/tests/e2e/test_simplekgpipeline_e2e.py
@@ -14,15 +14,23 @@
 #  limitations under the License.
 from __future__ import annotations
 
+from typing import Any
 from unittest.mock import MagicMock
 
 import neo4j
 import pytest
+from neo4j import Driver
 from neo4j_graphrag.experimental.components.types import LexicalGraphConfig
 from neo4j_graphrag.experimental.pipeline.kg_builder import SimpleKGPipeline
 from neo4j_graphrag.llm import LLMResponse
 
 
+@pytest.fixture(scope="function", autouse=True)
+def clear_db(driver: Driver) -> Any:
+    driver.execute_query("MATCH (n) DETACH DELETE n")
+    yield
+
+
 @pytest.mark.asyncio
 @pytest.mark.usefixtures("setup_neo4j_for_kg_construction")
 async def test_pipeline_builder_happy_path(
@@ -108,5 +116,147 @@ async def test_pipeline_builder_happy_path(
     )
 
     # Run the knowledge graph building process with text input
-    text_input = "John Doe lives in New York City."
-    await kg_builder_text.run_async(text=text_input)
+    await kg_builder_text.run_async(text=harry_potter_text)
+
+
+@pytest.mark.asyncio
+@pytest.mark.usefixtures("setup_neo4j_for_kg_construction")
+async def test_pipeline_builder_two_documents(
+    harry_potter_text_part1: str,
+    harry_potter_text_part2: str,
+    llm: MagicMock,
+    embedder: MagicMock,
+    driver: neo4j.Driver,
+) -> None:
+    """When everything works as expected, extracted entities, relations and text
+    chunks must be in the DB
+    """
+    driver.execute_query("MATCH (n) DETACH DELETE n")
+    embedder.embed_query.return_value = [1, 2, 3]
+    llm.ainvoke.side_effect = [
+        # first document
+        # first chunk
+        LLMResponse(
+            content="""{
+                        "nodes": [
+                            {
+                                "id": "0",
+                                "label": "Person",
+                                "properties": {
+                                    "name": "Harry Potter"
+                                }
+                            },
+                        ],
+                        "relationships": []
+                    }"""
+        ),
+        # second chunk
+        LLMResponse(content='{"nodes": [], "relationships": []}'),
+        # second document
+        # first chunk
+        LLMResponse(
+            content="""{
+                        "nodes": [
+                            {
+                                "id": "0",
+                                "label": "Person",
+                                "properties": {
+                                    "name": "Hermione Granger"
+                                }
+                            },
+                        ],
+                        "relationships": []
+                    }"""
+        ),
+        # second chunk
+        LLMResponse(content='{"nodes": [], "relationships": []}'),
+    ]
+
+    # Create an instance of the SimpleKGPipeline
+    kg_builder_text = SimpleKGPipeline(
+        llm=llm,
+        driver=driver,
+        embedder=embedder,
+        from_pdf=False,
+    )
+
+    # Run the knowledge graph building process with text input
+    await kg_builder_text.run_async(text=harry_potter_text_part1)
+    await kg_builder_text.run_async(text=harry_potter_text_part2)
+
+    # check graph content
+    records, _, _ = driver.execute_query("MATCH (n) RETURN n")
+    print(records)
+
+    assert False
+
+
+@pytest.mark.asyncio
+@pytest.mark.usefixtures("setup_neo4j_for_kg_construction")
+async def test_pipeline_builder_same_document_two_runs(
+    harry_potter_text_part1: str,
+    llm: MagicMock,
+    embedder: MagicMock,
+    driver: neo4j.Driver,
+) -> None:
+    """When everything works as expected, extracted entities, relations and text
+    chunks must be in the DB
+    """
+    driver.execute_query("MATCH (n) DETACH DELETE n")
+    embedder.embed_query.return_value = [1, 2, 3]
+    llm.ainvoke.side_effect = [
+        # first run
+        # first chunk
+        LLMResponse(
+            content="""{
+                        "nodes": [
+                            {
+                                "id": "0",
+                                "label": "Person",
+                                "properties": {
+                                    "name": "Harry Potter"
+                                }
+                            },
+                        ],
+                        "relationships": []
+                    }"""
+        ),
+        # second chunk
+        LLMResponse(content='{"nodes": [], "relationships": []}'),
+        # second run
+        # first chunk
+        LLMResponse(
+            content="""{
+                        "nodes": [
+                            {
+                                "id": "0",
+                                "label": "Person",
+                                "properties": {
+                                    "name": "Harry Potter"
+                                }
+                            },
+                        ],
+                        "relationships": []
+                    }"""
+        ),
+        # second chunk
+        LLMResponse(content='{"nodes": [], "relationships": []}'),
+    ]
+
+    # Create an instance of the SimpleKGPipeline
+    kg_builder_text = SimpleKGPipeline(
+        llm=llm,
+        driver=driver,
+        embedder=embedder,
+        from_pdf=False,
+    )
+
+    # Run the knowledge graph building process with text input
+    await kg_builder_text.run_async(text=harry_potter_text_part1)
+    await kg_builder_text.run_async(text=harry_potter_text_part1)
+
+    # check graph content
+    records, _, _ = driver.execute_query("MATCH (n) RETURN n")
+    print(records)
+
+    assert False
diff --git a/tests/unit/experimental/components/test_entity_relation_extractor.py b/tests/unit/experimental/components/test_entity_relation_extractor.py
index 29ba6568..a1371ec2 100644
--- a/tests/unit/experimental/components/test_entity_relation_extractor.py
+++ b/tests/unit/experimental/components/test_entity_relation_extractor.py
@@ -25,8 +25,8 @@
     balance_curly_braces,
     fix_invalid_json,
 )
-from neo4j_graphrag.experimental.components.pdf_loader import DocumentInfo
 from neo4j_graphrag.experimental.components.types import (
+    DocumentInfo,
     Neo4jGraph,
     TextChunk,
     TextChunks,
@@ -107,13 +107,13 @@ async def test_extractor_happy_path_non_empty_result() -> None:
     chunk_entity = result.nodes[1]
     assert chunk_entity.label == "Chunk"
     entity = result.nodes[2]
-    assert entity.id.endswith("0:0")
+    assert entity.id == f"{chunk_entity.id}:0"
     assert entity.label == "Person"
     assert entity.properties == {"chunk_index": 0}
     assert len(result.relationships) == 2
     assert result.relationships[0].type == "FROM_DOCUMENT"
-    assert result.relationships[0].start_node_id.endswith(":0")
-    assert result.relationships[0].end_node_id == "path"
+    assert result.relationships[0].start_node_id == f"{chunk_entity.id}"
+    assert result.relationships[0].end_node_id == f"{doc.id}"
     assert result.relationships[1].type == "FROM_CHUNK"
 
 
diff --git a/tests/unit/experimental/components/test_lexical_graph_builder.py b/tests/unit/experimental/components/test_lexical_graph_builder.py
index 4cedae61..4621c77e 100644
--- a/tests/unit/experimental/components/test_lexical_graph_builder.py
+++ b/tests/unit/experimental/components/test_lexical_graph_builder.py
@@ -14,14 +14,16 @@
 #  limitations under the License.
 from __future__ import annotations
 
+import uuid
+
 import pytest
 from neo4j_graphrag.experimental.components.lexical_graph import LexicalGraphBuilder
-from neo4j_graphrag.experimental.components.pdf_loader import DocumentInfo
 from neo4j_graphrag.experimental.components.types import (
     DEFAULT_CHUNK_NODE_LABEL,
     DEFAULT_CHUNK_TO_DOCUMENT_RELATIONSHIP_TYPE,
     DEFAULT_DOCUMENT_NODE_LABEL,
     DEFAULT_NEXT_CHUNK_RELATIONSHIP_TYPE,
+    DocumentInfo,
     GraphResult,
     LexicalGraphConfig,
     Neo4jNode,
@@ -31,33 +33,27 @@
 
 
 def test_lexical_graph_builder_create_chunk_node_no_metadata() -> None:
-    builder = LexicalGraphBuilder(
-        LexicalGraphConfig(id_prefix="test_create_chunk_node_no_metadata")
-    )
+    builder = LexicalGraphBuilder()
     node = builder.create_chunk_node(chunk=TextChunk(text="text chunk", index=0))
     assert isinstance(node, Neo4jNode)
-    assert node.id == "test_create_chunk_node_no_metadata:0"
+    assert node.id is not None
     assert node.properties == {"index": 0, "text": "text chunk"}
     assert node.embedding_properties == {}
 
 
 def test_lexical_graph_builder_create_chunk_node_metadata_no_embedding() -> None:
-    builder = LexicalGraphBuilder(
-        LexicalGraphConfig(id_prefix="test_create_chunk_node_metadata_no_embedding")
-    )
+    builder = LexicalGraphBuilder()
     node = builder.create_chunk_node(
         chunk=TextChunk(text="text chunk", index=0, metadata={"status": "ok"})
     )
     assert isinstance(node, Neo4jNode)
-    assert node.id == "test_create_chunk_node_metadata_no_embedding:0"
+    assert node.id is not None
     assert node.properties == {"index": 0, "text": "text chunk", "status": "ok"}
     assert node.embedding_properties == {}
 
 
 def test_lexical_graph_builder_create_chunk_node_metadata_embedding() -> None:
-    builder = LexicalGraphBuilder(
-        LexicalGraphConfig(id_prefix="test_create_chunk_node_metadata_embedding")
-    )
+    builder = LexicalGraphBuilder()
     node = builder.create_chunk_node(
         chunk=TextChunk(
             text="text chunk",
@@ -66,16 +62,15 @@ def test_lexical_graph_builder_create_chunk_node_metadata_embedding() -> None:
         ),
     )
     assert isinstance(node, Neo4jNode)
-    assert node.id == "test_create_chunk_node_metadata_embedding:0"
+    assert node.id is not None
     assert node.properties == {"index": 0, "text": "text chunk", "status": "ok"}
     assert node.embedding_properties == {"embedding": [1, 2, 3]}
 
 
 @pytest.mark.asyncio
 async def test_lexical_graph_builder_run_with_document() -> None:
-    lexical_graph_builder = LexicalGraphBuilder(
-        config=LexicalGraphConfig(id_prefix="test")
-    )
+    lexical_graph_builder = LexicalGraphBuilder()
+    doc_uid = str(uuid.uuid4())
     result = await lexical_graph_builder.run(
         text_chunks=TextChunks(
             chunks=[
@@ -83,31 +78,30 @@ async def test_lexical_graph_builder_run_with_document() -> None:
                 TextChunk(text="text chunk 1", index=1),
             ]
         ),
-        document_info=DocumentInfo(path="test_lexical_graph"),
+        document_info=DocumentInfo(path="test_lexical_graph", uid=doc_uid),
     )
     assert isinstance(result, GraphResult)
     graph = result.graph
     nodes = graph.nodes
     assert len(nodes) == 3
     document = nodes[0]
-    assert document.id == "test_lexical_graph"
+    assert document.id == doc_uid
     assert document.label == DEFAULT_DOCUMENT_NODE_LABEL
-    assert document.properties == {"path": "test_lexical_graph"}
+    assert document.properties["path"] == "test_lexical_graph"
+    assert document.properties["createdAt"] is not None
     chunk1 = nodes[1]
     assert chunk1.label == DEFAULT_CHUNK_NODE_LABEL
     chunk2 = nodes[2]
     assert chunk2.label == DEFAULT_CHUNK_NODE_LABEL
     assert len(graph.relationships) == 3
-    for relationship in graph.relationships[:2]:
-        assert relationship.type == DEFAULT_CHUNK_TO_DOCUMENT_RELATIONSHIP_TYPE
-    assert graph.relationships[2].type == DEFAULT_NEXT_CHUNK_RELATIONSHIP_TYPE
+    assert graph.relationships[0].type == DEFAULT_CHUNK_TO_DOCUMENT_RELATIONSHIP_TYPE
+    assert graph.relationships[1].type == DEFAULT_NEXT_CHUNK_RELATIONSHIP_TYPE
+    assert graph.relationships[2].type == DEFAULT_CHUNK_TO_DOCUMENT_RELATIONSHIP_TYPE
 
 
 @pytest.mark.asyncio
 async def test_lexical_graph_builder_run_no_document() -> None:
-    lexical_graph_builder = LexicalGraphBuilder(
-        config=LexicalGraphConfig(id_prefix="test")
-    )
+    lexical_graph_builder = LexicalGraphBuilder()
     result = await lexical_graph_builder.run(
         text_chunks=TextChunks(
             chunks=[
@@ -132,13 +126,13 @@ async def test_lexical_graph_builder_run_no_document() -> None:
 async def test_lexical_graph_builder_run_custom_labels() -> None:
     lexical_graph_builder = LexicalGraphBuilder(
         config=LexicalGraphConfig(
-            id_prefix="test",
             document_node_label="Report",
             chunk_node_label="Page",
             chunk_to_document_relationship_type="IN_REPORT",
             next_chunk_relationship_type="NEXT_PAGE",
         ),
     )
+    doc_uid = str(uuid.uuid4())
     result = await lexical_graph_builder.run(
         text_chunks=TextChunks(
             chunks=[
@@ -146,21 +140,21 @@ async def test_lexical_graph_builder_run_custom_labels() -> None:
                 TextChunk(text="text chunk 1", index=1),
             ]
         ),
-        document_info=DocumentInfo(path="test_lexical_graph"),
+        document_info=DocumentInfo(path="test_lexical_graph", uid=doc_uid),
     )
     assert isinstance(result, GraphResult)
     graph = result.graph
     nodes = graph.nodes
     assert len(nodes) == 3
     document = nodes[0]
-    assert document.id == "test_lexical_graph"
+    assert document.id == doc_uid
     assert document.label == "Report"
-    assert document.properties == {"path": "test_lexical_graph"}
+    assert document.properties["path"] == "test_lexical_graph"
     chunk1 = nodes[1]
     assert chunk1.label == "Page"
     chunk2 = nodes[2]
     assert chunk2.label == "Page"
     assert len(graph.relationships) == 3
-    for relationship in graph.relationships[:2]:
-        assert relationship.type == "IN_REPORT"
-    assert graph.relationships[2].type == "NEXT_PAGE"
+    assert graph.relationships[0].type == "IN_REPORT"
+    assert graph.relationships[1].type == "NEXT_PAGE"
+    assert graph.relationships[2].type == "IN_REPORT"
diff --git a/tests/unit/experimental/components/test_neo4j_reader.py b/tests/unit/experimental/components/test_neo4j_reader.py
index d80bc9a8..331d8073 100644
--- a/tests/unit/experimental/components/test_neo4j_reader.py
+++ b/tests/unit/experimental/components/test_neo4j_reader.py
@@ -41,9 +41,10 @@ async def test_neo4j_chunk_reader(driver: Mock) -> None:
     assert isinstance(res, TextChunks)
     assert len(res.chunks) == 1
     chunk = res.chunks[0]
+    assert chunk.uid == "azerty"
     assert chunk.text == "some text"
     assert chunk.index == 0
-    assert chunk.metadata == {"id": "azerty"}
+    assert chunk.metadata == {}
 
 
 @pytest.mark.asyncio
@@ -82,9 +83,10 @@ async def test_neo4j_chunk_reader_custom_lg_config(driver: Mock) -> None:
     assert isinstance(res, TextChunks)
     assert len(res.chunks) == 1
     chunk = res.chunks[0]
+    assert chunk.uid == "azerty"
     assert chunk.text == "some text"
     assert chunk.index == 0
-    assert chunk.metadata == {"id": "azerty", "other": "property"}
+    assert chunk.metadata == {"other": "property"}
 
 
 @pytest.mark.asyncio
@@ -118,10 +120,10 @@ async def test_neo4j_chunk_reader_fetch_embedding(driver: Mock) -> None:
     assert isinstance(res, TextChunks)
     assert len(res.chunks) == 1
     chunk = res.chunks[0]
+    assert chunk.uid == "azerty"
     assert chunk.text == "some text"
     assert chunk.index == 0
     assert chunk.metadata == {
         "other": "property",
-        "id": "azerty",
         "embedding": [1.0, 2.0, 3.0],
     }
diff --git a/tests/unit/experimental/components/text_splitters/test_fixed_size_splitter.py b/tests/unit/experimental/components/text_splitters/test_fixed_size_splitter.py
index 9c559874..0467201f 100644
--- a/tests/unit/experimental/components/text_splitters/test_fixed_size_splitter.py
+++ b/tests/unit/experimental/components/text_splitters/test_fixed_size_splitter.py
@@ -12,6 +12,8 @@
 #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
+from itertools import zip_longest
+
 import pytest
 from neo4j_graphrag.experimental.components.text_splitters.fixed_size_splitter import (
     FixedSizeSplitter,
@@ -34,7 +36,10 @@ async def test_split_text_no_overlap() -> None:
         TextChunk(text="nd sh", index=4),
         TextChunk(text="atter", index=5),
     ]
-    assert chunks.chunks == expected_chunks
+    for actual, expected in zip_longest(chunks.chunks, expected_chunks):
+        assert actual.text == expected.text
+        assert actual.index == expected.index
+        assert expected.uid is not None
 
 
 @pytest.mark.asyncio
@@ -50,7 +55,10 @@ async def test_split_text_with_overlap() -> None:
         TextChunk(text="ip and sha", index=2),
         TextChunk(text="hatter", index=3),
     ]
-    assert chunks.chunks == expected_chunks
+    for actual, expected in zip_longest(chunks.chunks, expected_chunks):
+        assert actual.text == expected.text
+        assert actual.index == expected.index
+        assert expected.uid is not None
 
 
 @pytest.mark.asyncio
diff --git a/tests/unit/llm/test_anthropic_llm.py b/tests/unit/llm/test_anthropic_llm.py
index fc8d2756..b1d583f6 100644
--- a/tests/unit/llm/test_anthropic_llm.py
+++ b/tests/unit/llm/test_anthropic_llm.py
@@ -18,7 +18,6 @@
 from unittest.mock import AsyncMock, MagicMock, Mock, patch
 
 import anthropic
-
 import pytest
 from neo4j_graphrag.exceptions import LLMGenerationError
 from neo4j_graphrag.llm.anthropic_llm import AnthropicLLM