Papers by Pramod Viswanath

2 papers
Preposition Sense Disambiguation and Representation (D18-1)

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Challenge: Prepositions are highly polysemous and their variegated senses encode significant semantic information.
Approach: They match each preposition’s context and their interplay to the geometry of the word vectors to the left and right of the preposition.
Outcome: The proposed algorithm is comparable to and better than state-of-the-art on two benchmark datasets.
Embedding Syntax and Semantics of Prepositions via Tensor Decomposition (N18-1)

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Challenge: Existing methods on preposition representation treat prepositions no different from content words (e.g., word2vec and GloVe).
Approach: They propose to use word-triple counts to capture a preposition’s interaction with its attachment and complement and derive preposition embeddings via tensor decomposition on a large unlabeled corpus.
Outcome: The proposed model is comparable to or better than the state-of-the-art on multiple standardized datasets.

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