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Ontology-Based Natural Language Texts Generation from Knowledge Base

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Open Semantic Technologies for Intelligent Systems (OSTIS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1625))

Abstract

In the knowledge-based intelligent system, the natural language interface is responsible for implementing communication between end-users and intelligent system using natural language. However the internal information of intelligent system is represented in a certain kind of specific format (knowledge base). When intelligent system need to exchange information with the end-users, it is necessary for natural language interface to obtain the ability to convert fragment of the knowledge base into natural language text. Due to the diversity and complexity of natural language, generating fluent, appropriate natural language text is still a significant challenge. By comparing other methods converting structured data into natural language text, this article describes the characteristics of fragment of knowledge base and the difficulties in natural language generation. The article proposed a unified semantic model to development of natural language generation component of natural language interface. The development of natural language generation component requires a combination of various types of knowledge about linguistics and various problem solving models oriented on natural language generation. In this article the main novelty is that in the unified semantic model the various approaches and linguistic knowledge about natural language generation can be integrated to generate natural language text from the fragment of knowledge base represented in graphical form.

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Authors and Affiliations

  1. Department of Intelligent Information Technology, Belarusian State University of Informatics and Radioelectronics, Minsk, Republic of Belarus

    Longwei Qian & Wenzu Li

Authors
  1. Longwei Qian
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  2. Wenzu Li
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Correspondence to Longwei Qian .

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Editors and Affiliations

  1. Belarusian State University of Informatics and Radioelectronics, Minsk, Belarus

    Vladimir Golenkov

  2. Belarusian State University, Minsk, Belarus

    Viktor Krasnoproshin

  3. Brest State Technical University, Brest, Belarus

    Vladimir Golovko

  4. Belarusian State University of Informatics and Radioelectronics, Minsk, Belarus

    Daniil Shunkevich

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Qian, L., Li, W. (2022). Ontology-Based Natural Language Texts Generation from Knowledge Base. In: Golenkov, V., Krasnoproshin, V., Golovko, V., Shunkevich, D. (eds) Open Semantic Technologies for Intelligent Systems. OSTIS 2021. Communications in Computer and Information Science, vol 1625. Springer, Cham. https://doi.org/10.1007/978-3-031-15882-7_12

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  • DOI: https://doi.org/10.1007/978-3-031-15882-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15881-0

  • Online ISBN: 978-3-031-15882-7

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