BERTopic n-gram words are not adjacent to each other

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After setting the ngram_range=(2,2), the trained BERTopic model generates topics with 2-gram phrases such as Topic_1: {"Model Router", "Network Setup", etc}, but the individual words of each 2-gram are not adjacent to each other within the document and they are far away form each other. It seems that the BERTopic model is not considering 2-gram at all. Is there any way to make sure that the individual words in the 2-gram phrases of each topic are not far away from each other within the related documents? I don't want BERTopic considers "Modem Router" as a 2-gram if there is no sentence in the whole document having "Modem" and "Router" words next to each other

Start by reproducing the reported BERTopic behavior with ngram_range=(2,2) and inspect how the trained model extracts topic phrases from related documents. No source file or test is named in the issue. Done should mean that a two-word topic phrase is formed only when its words occur adjacently in the document.

Written by the indexing model from the issue text.