How come same cluster category be separated?
This KMeans Clustering is a representative of points in the space based on 200 Features and their length. I think there is some gap in your perspective and the actual clustering.
 Other than &quot;Tram&quot;, most of the other relevant features are uncommon in both the Rail Cluster. So, two different blobs are created in space.
See this image, data are at the same place on the Tram dimension but other Features have created two different groups.

 These are the approaches, you may take -
 - Clean all the features for duplicate/similar meaning in the domain context e.g. rail, railway
 - Try different cluster count e.g. 5 and see if these two merges
 - Even if these are not merging then there is some message and you should figure it out. e.g. gvg, combino, streetcar, city