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Semantic Composition and Decomposition: From Recognition to Generation

Peter D. Turney

Published 2014 in arXiv.org

ABSTRACT

Semantic composition is the task of understanding the meaning of text by composing the meanings of the individual words in the text. Semantic decomposition is the task of understanding the meaning of an individual word by decomposing it into various aspects (factors, constituents, components) that are latent in the meaning of the word. We take a distributional approach to semantics, in which a word is represented by a context vector. Much recent work has considered the problem of recognizing compositions and decompositions, but we tackle the more dicult generation problem. For simplicity, we focus on noun-modier bigrams and noun unigrams. A test for semantic composition is, given context vectors for the noun and modier in a noun-modier bigram ( red salmon), generate a noun unigram that is synonymous with the given bigram (sockeye). A test for semantic decomposition is, given a context vector for a noun unigram (snifter), generate a noun-modier bigram that is synonymous with the given unigram ( brandy glass). With a vocabulary of about 73,000 unigrams from WordNet, there are 73,000 candidate unigram compositions for a bigram and 5,300,000,000 (73,000 squared) candidate bigram decompositions for a unigram. We generate ranked lists of potential solutions in two passes. A fast unsupervised learning algorithm generates an initial list of candidates and then a slower supervised learning algorithm renes the list. We evaluate the candidate solutions by comparing them to WordNet synonym sets. For decomposition (unigram to bigram), the top 100 most highly ranked bigrams include a WordNet synonym of the given unigram 50.7% of the time. For composition (bigram to unigram), the top 100 most highly ranked unigrams include a WordNet synonym of the given bigram 77.8% of the time.

PUBLICATION RECORD

  • Publication year

    2014

  • Venue

    arXiv.org

  • Publication date

    2014-05-30

  • Fields of study

    Linguistics, Computer Science

  • Identifiers
    arXiv 1405.7908
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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