Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
All-Instances Oblivious Chase Termination is Undecidable for Single-Head Binary TGDs
Authors: Bartosz Bednarczyk, Robert Ferens, Piotr Ostropolski-Nalewaja
IJCAI 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work, we show that undecidability occurs already for sets of single-head TGD over binary vocabularies. More precisely we are going to prove the following theorem: Theorem 1.1. All-Instances Oblivious Chase Termination is undecidable for sets of binary single-head TGDs. |
| Researcher Affiliation | Academia | 1Computational Logic Group, TU Dresden 2Institute of Computer Science, University of Wrocław |
| Pseudocode | No | The information is insufficient. The paper describes TGDs and chase procedures but does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The information is insufficient. The paper does not mention providing access to open-source code for the described methodology. |
| Open Datasets | No | The information is insufficient. The paper is theoretical and does not use or provide access information for a publicly available or open dataset for training purposes. |
| Dataset Splits | No | The information is insufficient. The paper is theoretical and does not involve empirical data splits for training, validation, or testing. |
| Hardware Specification | No | The information is insufficient. The paper is theoretical and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | The information is insufficient. The paper is theoretical and does not mention specific software dependencies with version numbers. |
| Experiment Setup | No | The information is insufficient. The paper is theoretical and does not describe any experimental setup details or hyperparameters. |