topic model trained on document-word co-occurrences will find topics that reflect broad thematic commonalities, the model trained on syntactic co-occurrences finds semantic classes that capture a much tighter sense of similarity: Words assigned high probability in the same topic tend to refer to entities that have similar properties, that perform similar actions, and have similar actions performed on them.
class 1 is represented by attack, raid, assault, campaign, and so on, forming a coherent semantic grouping.