mlsanityData to 14 Oct 2026

Natlog: a Lightweight Logic Programming Language with a Neuro-symbolic Touch

arXiv 2109.08291 ↗First posted 17 Sep 2021cs.PL cs.AI cs.LGcited by 5

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Abstract (arXiv)

We introduce Natlog, a lightweight Logic Programming language, sharing Prolog's unification-driven execution model, but with a simplified syntax and semantics. Our proof-of-concept Natlog implementation is tightly embedded in the Python-based deep-learning ecosystem with focus on content-driven indexing of ground term datasets. As an overriding of our symbolic indexing algorithm, the same function can be delegated to a neural network, serving ground facts to Natlog's resolution engine. Our open-source implementation is available as a Python package at https://pypi.org/project/natlog/ .

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 6 of its 22 references that are in the map. First posted on arXiv 17 Sep 2021.

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6 of 22 references.

References · 6

  1. 2019Neural Probabilistic Logic Programming in DeepProbLogcited by 394
  2. 2020Neurosymbolic AI: The 3rd Wavecited by 255
  3. 2020Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspectivecited by 95
  4. 2020From Statistical Relational to Neuro-Symbolic Artificial Intelligencecited by 63
  5. 2021Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use casescited by 39
  6. 2020eclingo: A solver for Epistemic Logic Programscited by 7

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Citing papers per year: 2022: 1; 2023: 2; 2024: 2.

5 papers.