BERT and English Grammar: What a Computer Learns About Syntax
BERT quietly surprised researchers by handling parts of English that many thought only humans master. I looked at three kinds of tests, from normal sentences to ones where words were swapped so meaning was gone, and some made by hand to probe tricky grammar. The result was clear: BERT often got the structure right, even when content words were jumbled. That tells us it has picked up real patterns of syntax, not just memorized phrases. In particular it did well on subject-verb agreement, and other puzzles about how words point back to each other. This matters because a good language model can help tools that write, translate, or check grammar for people. It not perfect, there are still mistakes, but the…
BERT and English Grammar: What a Computer Learns About Syntax
BERT quietly surprised researchers by handling parts of English that many thought only humans master. I looked at three kinds of tests, from normal sentences to ones where words were swapped so meaning was gone, and some made by hand to probe tricky grammar. The result was clear: BERT often got the structure right, even when content words were jumbled. That tells us it has picked up real patterns of syntax, not just memorized phrases. In particular it did well on subject-verb agreement, and other puzzles about how words point back to each other. This matters because a good language model can help tools that write, translate, or check grammar for people. It not perfect, there are still mistakes, but the progress is hopeful. Readable, simple tests revealed depth that was not obvious before, and made clear that machines are learning something like the rules we use when we speak and write.
Read article comprehensive review in Paperium.net: Assessing BERT’s Syntactic Abilities
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