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International Journal Of Literature And Languages

Peer Reviewed | Open Access | E-ISSN: 2771-2834
Published Article

UNLOCKING LINGUISTIC INSIGHTS: BRIDGING FRAMENET AND NATURAL LANGUAGE THROUGH THEMATIC ROLE STRUCTURES

UNLOCKING LINGUISTIC INSIGHTS: BRIDGING FRAMENET AND NATURAL LANGUAGE THROUGH THEMATIC ROLE STRUCTURES

Authors

  • Demir Aydin
    Associate Professor at The Department of Computer Programming of Trakya University, Turkey

DOI:

https://doi.org/10.37547/ijll/Volume03Issue10-01

Keywords:

Frame Net Thematic Role Structures Natural Language Analysis

Abstract

This study delves into the integration of Frame Net and natural language analysis through the innovative framework of Thematic Role Structures. By bridging the semantic world of Frame Net with the rich complexity of natural language, we unlock a wealth of linguistic insights. Thematic Role Structures offer a systematic and interpretable means of mapping verb-argument relationships, enabling enhanced information extraction, semantic parsing, and sentiment analysis. Through this interdisciplinary approach, we illuminate the potential for deeper linguistic understanding and demonstrate the applicability of Thematic Role Structures across diverse fields, including machine learning, computational linguistics, and beyond.

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