Named Entity Recognition
This is one of the first steps in the process of information extraction. Information extraction is the task of a machine extracting structured information from unstructured or semi-structured text. This furthers the comprehension of natural language by machines.
After text preprocessing and POS tagging, our corpus becomes semi-structured and machine-readable. Thus, information extraction is performed after we've readied our corpus.
The following diagram is an example of named entity recognition:
Figure 2.12: Example for named entity recognition
Named Entities
Named entities are real-world objects that can be classified into categories, such as people, places, and things. Basically, they are words that can be denoted by a proper name. Named entities can also include quantities, organizations, monetary values, and many more things.
Some examples of named entities and the categories they fall under are as follows:
- Donald Trump, person
- Italy, location...
