Integrating Conversational Entities and Dialogue Histories with Knowledge Graphs and Generative AI

Graham Wilcock; Kristiina Jokinen

Integrating Conversational Entities and Dialogue Histories with Knowledge Graphs and Generative AI

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

Existing methods for storing dialogue history and for tracking mentioned entities in spoken dialogues usually handle these tasks separately. Recent advances in knowledge graphs and generative AI make it possible to integrate them in a framework with a uniform representation for dialogue management. This may help to build more natural and grounded dialogue models that can reduce misunderstanding and lead to more reliable dialogue-based interactions with AI agents. The paper describes ongoing work on this approach.

Original language	English
Title of host publication	Proceedings Of The 15th International Workshop On Spoken Dialogue Systems Technology
Editors	Maria Ines Torres, Yuki Matsuda, Zoraida Callejas, Arantza DelPozo, Luis Fernando D'Haro
Number of pages	9
Place of Publication	Stroudsburg
Publisher	ACL
Publication date	2025
Pages	290-298
ISBN (Electronic)	979-8-89176-248-0
Publication status	Published - 2025
MoE publication type	A4 Article in conference proceedings
Event	International Workshop on Spoken Dialogue Systems Technology - Bilbao, Spain Duration: 27 May 2025 → 30 May 2025 Conference number: 15

Fields of Science

6121 Languages

Access to Document

2025.iwsds-1.31Final published version, 822 KBLicence: CC BY

Cite this

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title = "Integrating Conversational Entities and Dialogue Histories with Knowledge Graphs and Generative AI",

abstract = "Existing methods for storing dialogue history and for tracking mentioned entities in spoken dialogues usually handle these tasks separately. Recent advances in knowledge graphs and generative AI make it possible to integrate them in a framework with a uniform representation for dialogue management. This may help to build more natural and grounded dialogue models that can reduce misunderstanding and lead to more reliable dialogue-based interactions with AI agents. The paper describes ongoing work on this approach.",

keywords = "6121 Languages",

author = "Graham Wilcock and Kristiina Jokinen",

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editor = "Torres, \{Maria Ines\} and Yuki Matsuda and Zoraida Callejas and Arantza DelPozo and D'Haro, \{Luis Fernando\}",

booktitle = "Proceedings Of The 15th International Workshop On Spoken Dialogue Systems Technology",

publisher = "ACL",

address = "United States",

note = " International Workshop on Spoken Dialogue Systems Technology, IWSDS ; Conference date: 27-05-2025 Through 30-05-2025",

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Wilcock, G & Jokinen, K 2025, Integrating Conversational Entities and Dialogue Histories with Knowledge Graphs and Generative AI. in MI Torres, Y Matsuda, Z Callejas, A DelPozo & LF D'Haro (eds), Proceedings Of The 15th International Workshop On Spoken Dialogue Systems Technology. ACL, Stroudsburg, pp. 290-298, International Workshop on Spoken Dialogue Systems Technology, Bilbao, Spain, 27/05/2025.

Integrating Conversational Entities and Dialogue Histories with Knowledge Graphs and Generative AI. / Wilcock, Graham ; Jokinen, Kristiina.
Proceedings Of The 15th International Workshop On Spoken Dialogue Systems Technology. ed. / Maria Ines Torres; Yuki Matsuda; Zoraida Callejas; Arantza DelPozo; Luis Fernando D'Haro. Stroudsburg: ACL, 2025. p. 290-298.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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N2 - Existing methods for storing dialogue history and for tracking mentioned entities in spoken dialogues usually handle these tasks separately. Recent advances in knowledge graphs and generative AI make it possible to integrate them in a framework with a uniform representation for dialogue management. This may help to build more natural and grounded dialogue models that can reduce misunderstanding and lead to more reliable dialogue-based interactions with AI agents. The paper describes ongoing work on this approach.

AB - Existing methods for storing dialogue history and for tracking mentioned entities in spoken dialogues usually handle these tasks separately. Recent advances in knowledge graphs and generative AI make it possible to integrate them in a framework with a uniform representation for dialogue management. This may help to build more natural and grounded dialogue models that can reduce misunderstanding and lead to more reliable dialogue-based interactions with AI agents. The paper describes ongoing work on this approach.

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BT - Proceedings Of The 15th International Workshop On Spoken Dialogue Systems Technology

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