diff --git a/src/lang_main/analysis/graphs.py b/src/lang_main/analysis/graphs.py
index 13425ba..64fb6d3 100644
--- a/src/lang_main/analysis/graphs.py
+++ b/src/lang_main/analysis/graphs.py
@@ -282,7 +282,7 @@ def filter_graph_by_node_degree(
 
 def filter_graph_by_number_edges(
     graph: TokenGraph,
-    limit: int,
+    limit: int | None,
     property: str = 'weight',
     descending: bool = True,
 ) -> TokenGraph:
@@ -290,7 +290,10 @@ def filter_graph_by_number_edges(
     # edges
     original = set(graph.edges(data=property))  # type: ignore
     original_sorted = sorted(original, key=lambda tup: tup[2], reverse=descending)
-    chosen = set(original_sorted[:limit])
+    if limit is not None:
+        chosen = set(original_sorted[:limit])
+    else:
+        chosen = set(original_sorted)
     edges_to_drop = original.difference(chosen)
     graph.remove_edges_from(edges_to_drop)
 
diff --git a/src/lang_main/constants.py b/src/lang_main/constants.py
index 88263b1..9dab9ed 100644
--- a/src/lang_main/constants.py
+++ b/src/lang_main/constants.py
@@ -1,7 +1,7 @@
 from enum import Enum  # noqa: I001
 from importlib.util import find_spec
 from pathlib import Path
-from typing import Final
+from typing import Final, cast
 import os
 
 from sentence_transformers import SimilarityFunction
@@ -19,7 +19,7 @@ from lang_main.types import (
     STFRDeviceTypes,
     STFRModelArgs,
     STFRModelTypes,
-    STFRQuantFilenames,  # noqa: F401
+    STFRONNXFilenames,  # noqa: F401
     SpacyModelTypes,
 )
 
@@ -85,7 +85,7 @@ os.environ['SENTENCE_TRANSFORMERS_HOME'] = str(MODEL_BASE_FOLDER)
 # LANG_MAIN_STFR_BACKEND : STFR backend, choice between "torch" and "onnx"
 
 SPACY_MODEL_NAME: Final[str | SpacyModelTypes] = os.environ.get(
-    'LANG_MAIN_SPACY_MODEL', SpacyModelTypes.DE_CORE_NEWS_SM
+    'LANG_MAIN_SPACY_MODEL', SpacyModelTypes.DE_DEP_NEWS_TRF
 )
 STFR_MODEL_NAME: Final[str | STFRModelTypes] = os.environ.get(
     'LANG_MAIN_STFR_MODEL', STFRModelTypes.E5_BASE_STS_EN_DE
@@ -95,12 +95,12 @@ STFR_CUSTOM_MODELS: Final[dict[tuple[STFRModelTypes, STFRBackends], bool]] = {
 }
 STFR_DEVICE: Final[STFRDeviceTypes] = STFRDeviceTypes.CPU
 STFR_SIMILARITY: Final[SimilarityFunction] = SimilarityFunction.COSINE
-STFR_BACKEND: Final[str | STFRBackends] = os.environ.get(
-    'LANG_MAIN_STFR_BACKEND', STFRBackends.TORCH
+STFR_BACKEND: Final[STFRBackends] = cast(
+    STFRBackends, os.environ.get('LANG_MAIN_STFR_BACKEND', STFRBackends.TORCH)
 )
 stfr_model_args_default: STFRModelArgs = {'torch_dtype': 'float32'}
 stfr_model_args_onnx: STFRModelArgs = {
-    'file_name': STFRQuantFilenames.ONNX_Q_UINT8,
+    'file_name': STFRONNXFilenames.ONNX_Q_UINT8,
     'provider': ONNXExecutionProvider.CPU,
     'export': False,
 }
@@ -131,7 +131,11 @@ THRESHOLD_SIMILARITY: Final[float] = CONFIG['preprocess']['threshold_similarity'
 
 # ** graph postprocessing
 EDGE_WEIGHT_DECIMALS: Final[int] = 4
-THRESHOLD_EDGE_NUMBER: Final[int] = CONFIG['graph_postprocessing']['threshold_edge_number']
+threshold_edge_number: int | None = None
+cfg_threshold_edge_number: int = CONFIG['graph_postprocessing']['threshold_edge_number']
+if cfg_threshold_edge_number >= 0:
+    threshold_edge_number = cfg_threshold_edge_number
+THRESHOLD_EDGE_NUMBER: Final[int | None] = threshold_edge_number
 PROPERTY_NAME_DEGREE_WEIGHTED: Final[str] = 'degree_weighted'
 PROPERTY_NAME_BETWEENNESS_CENTRALITY: Final[str] = 'betweenness_centrality'
 PROPERTY_NAME_IMPORTANCE: Final[str] = 'importance'
diff --git a/src/lang_main/lang_main_config.toml b/src/lang_main/lang_main_config.toml
index 7b187f0..ca63d52 100644
--- a/src/lang_main/lang_main_config.toml
+++ b/src/lang_main/lang_main_config.toml
@@ -29,7 +29,7 @@ date_cols = [
     "ErstellungsDatum",
 ]
 threshold_amount_characters = 5
-threshold_similarity = 0.8
+threshold_similarity = 0.9
 
 [graph_postprocessing]
 threshold_edge_number = 330