Shallow parsing

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Shallow parsing (also chunking or light

topic modeling, etc.) can take contextual information into account and thus compose chunks in such a way that they better reflect the semantic relations between the basic constituents.[1]
That is, these more advanced methods get around the problem that combinations of elementary constituents can have different higher level meanings depending on the context of the sentence.

It is a technique widely used in natural language processing. It is similar to the concept of lexical analysis for computer languages. Under the name "shallow structure hypothesis", it is also used as an explanation for why second language learners often fail to parse complex sentences correctly.[2]

References

Citations

  1. Jurafsky, Daniel
    ; Martin, James H. (2000). Speech and Language Processing. Singapore: Pearson Education Inc. pp. 577–586.
  2. S2CID 15990215.{{cite journal}}: CS1 maint: multiple names: authors list (link
    )

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See also