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You're reading from  Hands-On Natural Language Processing with PyTorch 1.x

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Published inJul 2020
Reading LevelBeginner
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ISBN-139781789802740
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Thomas Dop
Thomas Dop
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Thomas Dop

Thomas Dop is a data scientist at MagicLab, a company that creates leading dating apps, including Bumble and Badoo. He works on a variety of areas within data science, including NLP, deep learning, computer vision, and predictive modeling. He holds an MSc in data science from the University of Amsterdam.
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Tagging and chunking for parts of speech

So far, we have covered several approaches for representing words and sentences, including bag-of-words, embeddings, and n-grams. However, these representations fail to capture the structure of any given sentence. Within natural language, different words can have different functions within a sentence. Consider the following:

The big dog is sleeping on the bed

We can "tag" the various words of this text, depending on the function of each word in the sentence. So, the preceding sentence becomes as follows:

The -> big -> dog -> is -> sleeping -> on -> the -> bed

Determiner -> Adjective -> Noun -> Verb -> Verb -> Preposition -> Determiner-> Noun

These parts of speech include, but are not limited to, the following:

Figure 3.24 – Parts of speech

These different parts of speech can be used to better understand the structure of sentences. For example,...

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Hands-On Natural Language Processing with PyTorch 1.x
Published in: Jul 2020Publisher: PacktISBN-13: 9781789802740

Author (1)

author image
Thomas Dop

Thomas Dop is a data scientist at MagicLab, a company that creates leading dating apps, including Bumble and Badoo. He works on a variety of areas within data science, including NLP, deep learning, computer vision, and predictive modeling. He holds an MSc in data science from the University of Amsterdam.
Read more about Thomas Dop