Papers with document embedding methods

    1 papers
    Learning Outside the Box: Discourse-level Features Improve Metaphor Identification (N19-1)

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    Challenge: Current approaches to metaphor identification use restricted linguistic contexts, e.g. by only considering a verb’s arguments or the sentence containing a phrase.
    Approach: They propose to train simple gradient boosting classifiers on representations of an utterance and its surrounding discourse learned with a variety of document embedding methods.
    Outcome: The proposed classifiers obtained state-of-the-art results on the 2018 VU Amsterdam metaphor identification task without complex metaphor-specific features or deep neural architectures employed by other systems.

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