Detection of Domain-Specific Hypernyms Using Named Entity Recognition and Extraction

This paper explores the task of hypernym detection in the medical domain, leveraging natural language processing techniques and machine learning. We address this challenge by presenting a solution to the SemEval-2018 Task 9: Hypernym Discovery, focusing on identifying hypernyms for specific terms within a given search space. Our approach involves integrating pattern-based and distributional methods to achieve wider coverage while maintaining accuracy. We illustrate the process of hypernym detection as a sentence segmentation problem, where each word is labeled based on its semantic category. Through empirical evaluation, we demonstrate the effectiveness of our proposed solution, highlighting its performance metrics and execution times.