What is Coreference Resolution and how to apply it?

What is Coreference Resolution and how to apply it?

What is Coreference Resolution and how to apply it?

This recipe explains what is Coreference Resolution and how to apply it


Recipe Objective

What is Coreference Resolution and how to apply it? Coreference Resolution is nothing but the task of clustering mentions in text that will refer to the same necessary real-world entities.

Coreference Resolution is amazing to find the complex relationship between the 'signifier' and the 'signified',i.e., which expression or phrase refers to a particular entity in a text. Important for tasks like document summarization, question answering, and information extraction.

For e.g. Heena went to Jason's store to buy the new table. She looked at it for an hour.

Here from the above, we humans can quickly identify "Heena" and "She" belongs to the same cluster that means "She" denotes Heena also "table" and "it" belongs to the same cluster as "it" denotes the table(and not Jason's store).

This Job is done automatically with the help of Coreference Resolution which is a component of NLP.

Step 1 - Install the CoreNLP stanford for Coreference Resolution

!pip install stanford-corenlp

The above package is a python interface for Stanford CoreNLP, which will containing a refernece implementation to interface with the Stanford CoreNLP Server.

Step 2 - Install the coregraph for Coreference Resolution

!pip install corefgraph

This package performs the Coreference Resolution task, It is an independent python module

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