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Bangla-REX: A distinct dataset for Bangla relation extraction.

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Summary

Bangla REX is a new dataset for relation extraction in the Bangla language, featuring over 90,000 text entries and a knowledge base. This resource aims to advance Bangla natural language processing (NLP) research and applications.

Keywords:
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Area of Science:

  • Natural Language Processing (NLP)
  • Computational Linguistics
  • Information Extraction

Background:

  • Lack of specialized datasets for relation extraction in the Bangla language.
  • Need for structured resources to support advanced NLP tasks in Bangla.
  • Growing importance of multilingual NLP and information processing.

Purpose of the Study:

  • Introduce Bangla REX, a comprehensive dataset for Bangla relation extraction.
  • Provide a structured corpus and knowledge base to facilitate NLP research.
  • Enable accurate extraction and classification of semantic relations in Bangla text.

Main Methods:

  • Compilation of 90,441 text entries from reliable sources like Bangla Wikipedia and Wikidata.
  • Development of a Bangla Knowledge Base (KB) with 63,256 entries for automated annotation.
  • Annotation of the dataset with various relation tags, including movie actors, locations, and company information.

Main Results:

  • Creation of a large-scale, structured dataset (Bangla REX) for relation extraction tasks.
  • Development of an accompanying Bangla Knowledge Base to aid in corpus annotation.
  • Inclusion of diverse relation categories crucial for semantic understanding.

Conclusions:

  • Bangla REX addresses a critical resource gap for Bangla NLP.
  • The dataset provides a valuable benchmark for training and evaluating relation extraction models.
  • This resource is expected to foster innovation in Bangla NLP and multilingual information processing.