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CHAPTER Vector Semantics and Embeddings

Speech and Language Processing. Daniel Jurafsky & James H. Martin. Copyright 2021. Allrights reserved. Draft of December 29, Semantics andEmbeddings Nets are for fish;Once you get the fish, you can forget the net. Words are for meaning;Once you get the meaning, you can forget the words (Zhuangzi), CHAPTER 26 The asphalt that Los Angeles is famous for occurs mainly on its freeways. Butin the middle of the city is another patch of asphalt, the La Brea tar pits, and thisasphalt preserves millions of fossil bones from the last of the Ice Ages of the Pleis-tocene Epoch. One of these fossils is theSmilodon, or saber-toothed tiger, instantlyrecognizable by its long canines.

embeddings hypothesis by learning representations of the meaning of words, called embeddings, directly from their distributions in texts. These representations are used in every nat-ural language processing application that makes use of meaning, and the static em-beddings we introduce here underlie the more powerful dynamic or contextualized

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