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DOI: 10.4230/LIPIcs.TIME.2025.15

The Temporal Vadalog System (Short Paper)

Authors: Luigi Bellomarini, Livia Blasi, Markus Nissl, and Emanuel Sallinger

Published in: LIPIcs, Volume 355, 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)

Abstract

The recent resurgence of the Datalog language in the Knowledge Representation and Reasoning community has paved the way for a very promising proposal for temporal extension. DatalogMTL (Datalog with Metric Temporal Operators) is a language that offers a good trade-off between computational complexity and expressive power. However, existing implementations are still preliminary or prototypical. In this extended abstract, we give a brief overview of Temporal Vadalog, a system supporting reasoning over DatalogMTL programs built upon an engineered architecture and adopted in production scenarios in the financial setting.

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Luigi Bellomarini, Livia Blasi, Markus Nissl, and Emanuel Sallinger. The Temporal Vadalog System (Short Paper). In 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 355, pp. 15:1-15:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{bellomarini_et_al:LIPIcs.TIME.2025.15,
  author =	{Bellomarini, Luigi and Blasi, Livia and Nissl, Markus and Sallinger, Emanuel},
  title =	{{The Temporal Vadalog System}},
  booktitle =	{32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)},
  pages =	{15:1--15:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-401-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{355},
  editor =	{Vidal, Thierry and Wa{\l}\k{e}ga, Przemys{\l}aw Andrzej},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2025.15},
  URN =		{urn:nbn:de:0030-drops-244611},
  doi =		{10.4230/LIPIcs.TIME.2025.15},
  annote =	{Keywords: temporal reasoning, Datalog, DatalogMTL}
}

Document

DOI: 10.4230/OASIcs.Tannen.1

Explaining Enterprise Knowledge Graphs with Large Language Models and Ontological Reasoning

Authors: Teodoro Baldazzi, Luigi Bellomarini, Stefano Ceri, Andrea Colombo, Andrea Gentili, Emanuel Sallinger, and Paolo Atzeni

Published in: OASIcs, Volume 119, The Provenance of Elegance in Computation - Essays Dedicated to Val Tannen (2024)

Abstract

In recent times, the demand for transparency and accountability in AI-driven decisions has intensified, particularly in high-stakes domains like finance and bio-medicine. This focus on the provenance of AI-generated conclusions underscores the need for decision-making processes that are not only transparent but also readily interpretable by humans, to built trust of both users and stakeholders. In this context, the integration of state-of-the-art Large Language Models (LLMs) with logic-oriented Enterprise Knowledge Graphs (EKGs) and the broader scope of Knowledge Representation and Reasoning (KRR) methodologies is currently at the cutting edge of industrial and academic research across numerous data-intensive areas. Indeed, such a synergy is paramount as LLMs bring a layer of adaptability and human-centric understanding that complements the structured insights of EKGs. Conversely, the central role of ontological reasoning is to capture the domain knowledge, accurately handling complex tasks over a given realm of interest, and to infuse the process with transparency and a clear provenance-based explanation of the conclusions drawn, addressing the fundamental challenge of LLMs' inherent opacity and fostering trust and accountability in AI applications. In this paper, we propose a novel neuro-symbolic framework that leverages the underpinnings of provenance in ontological reasoning to enhance state-of-the-art LLMs with domain awareness and explainability, enabling them to act as natural language interfaces to EKGs.

Cite as

Teodoro Baldazzi, Luigi Bellomarini, Stefano Ceri, Andrea Colombo, Andrea Gentili, Emanuel Sallinger, and Paolo Atzeni. Explaining Enterprise Knowledge Graphs with Large Language Models and Ontological Reasoning. In The Provenance of Elegance in Computation - Essays Dedicated to Val Tannen. Open Access Series in Informatics (OASIcs), Volume 119, pp. 1:1-1:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{baldazzi_et_al:OASIcs.Tannen.1,
  author =	{Baldazzi, Teodoro and Bellomarini, Luigi and Ceri, Stefano and Colombo, Andrea and Gentili, Andrea and Sallinger, Emanuel and Atzeni, Paolo},
  title =	{{Explaining Enterprise Knowledge Graphs with Large Language Models and Ontological Reasoning}},
  booktitle =	{The Provenance of Elegance in Computation - Essays Dedicated to Val Tannen},
  pages =	{1:1--1:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-320-1},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{119},
  editor =	{Amarilli, Antoine and Deutsch, Alin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Tannen.1},
  URN =		{urn:nbn:de:0030-drops-200971},
  doi =		{10.4230/OASIcs.Tannen.1},
  annote =	{Keywords: provenance, ontological reasoning, language models, knowledge graphs}
}

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Documents authored by Bellomarini, Luigi

The Temporal Vadalog System (Short Paper)

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Explaining Enterprise Knowledge Graphs with Large Language Models and Ontological Reasoning

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