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Natural Language Processing with Java

You're reading from   Natural Language Processing with Java Explore various approaches to organize and extract useful text from unstructured data using Java

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Product type Paperback
Published in Mar 2015
Publisher
ISBN-13 9781784391799
Length 262 pages
Edition 1st Edition
Languages
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Authors (2):
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Richard M. Reese Richard M. Reese
Author Profile Icon Richard M. Reese
Richard M. Reese
Richard M Reese Richard M Reese
Author Profile Icon Richard M Reese
Richard M Reese
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Toc

Why NER is difficult?

Like many NLP tasks, NER is not always simple. Although the tokenization of a text will reveal its components, understanding what they are can be difficult. Using proper nouns will not always work because of the ambiguity of language. For example, Penny and Faith, while valid names, they may also be used for a measurement of currency and a belief, respectively. We can also find words such as Georgia are used as a name of a country, a state, and a person.

Some phrases can be challenging. The phrase "Metropolitan Convention and Exhibit Hall" may contain words that in themselves are valid entities. When the domain is well known, a list of entities can be very useful and easy to implement.

NER is typically applied at the sentence level, otherwise a phrase can easily span a sentence leading to incorrect identification of an entity. For example, in the following sentence:

"Bob went south. Dakota went west."

If we ignored the sentence boundaries, then we...

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