From ContE to Entity Type Embeddings in Natural Language Processing
Last Updated on July 24, 2023 by Editorial Team
Author(s): Edward Ma
Originally published on Towards AI.
Photo by twinsfisch on Unsplash
In the previous story, TransE (Border et al., 2013) use a translating mechanism to transform subject (s) by the predicate (p) to object (o). Just like word2vec, we can compute “Queen” by using “King” + “Man” embeddings.
Word2vec Sample: King + Woman ~= Queen (source)
Moon et al. (2017) consider contextual relation to solving graph completion. Authors consider not only the triplet (s, p, o) but also outgoing relation types (from s) and incoming relation types (to o).
Contextual relation for a triple (s, p, o). (Moon et al., 2017)
When two entities (“Alex Guinness” and “Star Wars”) have relations… Read the full blog for free on Medium.
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