How to Tag Entities in String spaCy

Entities are specific pieces of information that can be extracted from a text. They can be categorized into different types: person, location, organization, event, product etc. These are some common entity types, but other entities may depend on the specific use case or domain.  

Tagging entities in a string, also known as named-entity recognition (NER), is a way to extract structured information from unstructured text. Tagging entities involves identifying and classifying specific pieces of information, such as people, places, and organizations, and labeling them with specific tags or labels. There are several ways to tag entities in a string, some of which include:  

• Regular expressions: This method uses pattern matching to identify entities in a string.  
• Named Entity Recognition (NER): This method uses machine learning algorithms to identify entities in a string. It is commonly used in natural language processing tasks.  
• Dictionary or lookup-based method: This method uses a pre-defined dictionary or lookup table to match entities in a string.  

You may have a look at the code below for more information about tagging entities in string.

Preview of the output that you will get on running this code from your IDE

Code

In this solution we have used Spacy library.

1. Copy the code using the "Copy" button above, and paste it in a Python file in your IDE.
2. Enter the Text
3. Run the file to Tag the entities in the string

I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.

I found this code snippet by searching for "Tag entities in the string using Spacy " in kandi. You can try any such use case!

Note

In this snippet we are using a Language model (en_core_web_sm)

1. Download the model using the command python -m spacy download en_core_web_sm .
2. paste it in your terminal and download it.

Check the user's spacy version using pip show spacy command in users terminal.

1. if its version 3.0, you will need to load it using nlp = spacy.load("en_core_web_sm")
2. if its version is less than 3.0 you will need to load it using nlp = spacy.load("en")

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

1. The solution is created in Python 3.7.15 Version
2. The solution is tested on Spacy 3.4.3 Version

Using this solution, tag entities in the string with the help of regular expression function in spacy . This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us to tag the entities in python.

Dependent Library

If you do not have SpaCy that is required to run this code, you can install it by clicking on the above link and copying the pip Install command from the Spacy page in kandi.

You can search for any dependent library on kandi like Spacy

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