Transcription of CHAPTER Vector Semantics and Embeddings
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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.
6.1 Lexical Semantics Let’s begin by introducing some basic principles of word meaning. How should we represent the meaning of a word? In the n-gram models of Chapter 3, and in classical NLP applications, our only representation of a word is as a string of letters, or an index in a vocabulary list. This representation is not that different from a
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