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arXiv · 1702.06696

One Representation per Word - Does it make Sense for Composition?

Thomas Kober·Julie Weeds·John Wilkie·Jeremy Reffin·David Weir
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Abstract

In this paper, we investigate whether an a priori disambiguation of word senses is strictly necessary or whether the meaning of a word in context can be disambiguated through composition alone. We evaluate the performance of off-the-shelf single-vector and multi-sense vector models on a benchmark phrase similarity task and a novel task for word-sense discrimination. We find that single-sense vector models perform as well or better than multi-sense vector models despite arguably less clean elementary representations. Our findings furthermore show that simple composition functions such as pointwise addition are able to recover sense specific information from a single-sense vector model remarkably well.

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Thomas Kober, Julie Weeds, John Wilkie, Jeremy Reffin, David Weir. 2017-02-22. One Representation per Word - Does it make Sense for Composition?. https://arxiv.org/abs/1702.06696

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