Analogy-based explanation evaluation dataset for HCOMP 2022 paper "It Is Like Finding a Polar Bear in the Savannah! Concept-level AI Explanations with Analogical Inference from Commonsense Knowledge."

DOI:10.4121/de1df5c0-5430-40f9-ba9a-ba0d1f415f28.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/de1df5c0-5430-40f9-ba9a-ba0d1f415f28

Datacite citation style

He, Gaole; Balayn, Agathe; Buijsman, Stefan; Jie Yang; Gadiraju, Ujwal (2025): Analogy-based explanation evaluation dataset for HCOMP 2022 paper "It Is Like Finding a Polar Bear in the Savannah! Concept-level AI Explanations with Analogical Inference from Commonsense Knowledge.". Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/de1df5c0-5430-40f9-ba9a-ba0d1f415f28.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Software

This repo contains all code and data associated with the paper "It Is Like Finding a Polar Bear in the Savannah! Concept-level AI Explanations with Analogical Inference from Commonsense Knowledge." The dataset mainly contains generated analogies and expert evaluations from five colleagues in TU Delft. Our experimental results indicate that the proposed qualitative dimensions can positively contribute to the perceived helpfulness of analogy-based explanations.

History

  • 2025-02-06 first online, published, posted

Publisher

4TU.ResearchData

Format

table/csv

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Software Technology, Web Information Systems Group

DATA

To access the source code, use the following command:

git clone https://data.4tu.nl/v3/datasets/d6208c6f-50b0-42a9-84f5-0da1d39bc805.git "HCOMP2022_ARCHIE"

Or download the latest commit as a ZIP.

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