Copy edit: reduce dash overuse in prose

README.md

@@ -145,7 +145,7 @@ category).
 
 ### Out-of-Scope Use
 
-Any commercial use — the source license (CC BY-NC 3.0) is non-commercial
+Any commercial use. The source license (CC BY-NC 3.0) is non-commercial
 only. The dataset is not intended or suitable for identifying individuals;
 it contains no personal or sensitive data by design (aerial images of
 power line hardware only). Asset appearance reflects a specific utility
@@ -178,7 +178,7 @@ samples).
 
 - `ground_truth` uses `Detections` because InsPLAD-det's source annotations
   are 2D bounding boxes (no segmentation masks, despite the COCO schema
-  having a `segmentation` field — it is always empty in the source data).
+  having a `segmentation` field; it is always empty in the source data).
 - `fault` and `anomaly` use `Classification` (not `Classifications`)
   because each cropped image in these sub-datasets carries exactly one
   label, encoded by its containing folder in the source data.
@@ -229,8 +229,8 @@ Automated visual inspection of power line assets is an active research
 area, but most power line inspection datasets are proprietary, undisclosed
 by the utility companies and agencies that hold them. InsPLAD was created
 to provide the first large, real-world, publicly available dataset and
-benchmark covering all three stages of a typical inspection pipeline —
-asset detection, defect classification, and anomaly detection — on the
+benchmark covering all three stages of a typical inspection pipeline
+(asset detection, defect classification, and anomaly detection) on the
 same underlying asset categories.
 
 ### Source Data