Entity linking, also known as entity identification or entity recognition, is the process of identifying specific entities in a text in order to provide a link to additional information about that entity. This additional information is often found in knowledge bases such as Wikipedia, or dictionaries related to the particular field the text belongs to. One of the most widely used methods of entity linking requires the presence of Named Entity Recognition (NER) technology.
Entity linking is a common component of Natural Language Processing (NLP) applications. It can be used in tasks such as content understanding and sentiment analysis. Furthermore, entity linking is a key component in tasks such as Automatic Text Summarization, Machine Translation, Question Answering and Text Classification.
In the context of the computing industry, entity linking is typically used to link phrases or words with concepts related to the computer. For example, a computer retailer’s website might use entity linking to link the word “hard drive” to the relevant product page, giving customers an easy way to navigate the website and find the information or product they are looking for.
Entity linking is also often used in computer-based dictionaries and encyclopedias in order to link words and concepts with more detailed, related information. This provides users with an efficient way to learn additional information about the concept or word they are researching, saving time and effort when trying to understand or contextualise a concept.
In conclusion, entity linking is an increasingly important part of natural language processing applications, especially in the computing industry, as it allows for efficient and accurate linking of words and concepts with related information. This can help customers navigate a website and quickly find specific product information, as well as providing useful information for encyclopedia and dictionary users.
