Course Q&A

My answer is:
In computational linguistics, algorithms resolve word ambiguity by analyzing the "semantic signals" provided by surrounding words, known as collocations. In the fisherman example, the computer weighs the conflicting signals of "deposit" against "fisherman," "catch," and "current." Using Word Sense Disambiguation (WSD) and contextual embeddings, the system calculates which sense has the highest statistical probability within that specific context. Ultimately, the machine selects the "river bank" definition because the collective weight of the geographic terms mathematically overrides the single financial reference.
How about you?