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Knowledge-Driven Event Extraction in Russian: Corpus-Based Linguistic Resources.

Valery Solovyev1, Vladimir Ivanov1

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This study introduces essential linguistic resources for Russian event extraction systems. It proposes novel methods for creating these resources, enabling knowledge acquisition in new languages.

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Area of Science:

  • Natural Language Processing (NLP)
  • Computational Linguistics
  • Knowledge Acquisition

Background:

  • Automatic event extraction is crucial for knowledge acquisition and knowledge base population.
  • Developing event extraction systems often requires extensive manual effort in corpus annotation and resource creation.
  • Existing research primarily focuses on adapting English-based systems, neglecting event extraction in other languages due to resource scarcity.

Purpose of the Study:

  • To define necessary linguistic resources for developing a knowledge-based event extraction system in Russian.
  • To propose methods for creating these resources in Russian and other languages.
  • To evaluate the proposed methods through the development of a Russian event extraction system.

Main Methods:

  • Definition of key linguistic resources: subordination models, event triggers, and Frame Elements.
  • Development of methods for resource creation utilizing the Google Books NGram Corpus.
  • Implementation and evaluation of an event extraction system for the Russian language.

Main Results:

  • Successful definition of essential linguistic resources for Russian event extraction.
  • Demonstration of effective methods for creating these resources using a large-scale corpus.
  • Validation of the methods through the development of a functional Russian event extraction system.

Conclusions:

  • The proposed linguistic resources and creation methods are vital for advancing event extraction in Russian.
  • These methods offer a scalable approach for developing event extraction systems in under-resourced languages.
  • This work facilitates knowledge acquisition and knowledge base population for non-English languages.