Abstract
Adding to the budding landscape of advanced analysis tools for Probabilistic Soft Logic (PSL), we present a graphical explorer for grounded PSL models. It exposes the structure of the model from the perspective of any single atom, listing the ground rules in which it occurs. The other atoms in these rules serve as links for navigation through the resulting rule-atom graph (RAG). As additional diagnostic criteria, each associated rule is further classified as exerting upward or downward pressure on the atom’s value, and as active or inactive depending on its importance for the MAP estimate.
Our RAG viewer further includes a general infrastructure for making PSL results explainable by stating the reasoning patterns in terms of domain language. For this purpose, we provide a Java interface for “talking” predicates and rules which can generate verbalized explanations of the atom interactions effected by each rule. If the model’s rules are structured similarly to the way the domain is conceptualized by users, they will receive an intuitive explanation of the result in natural language.
As an example application, we present the current state of the loanword detection component of EtInEn, our upcoming software for machine-assisted etymological theory development.
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Acknowledgements
This work has been funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (CrossLingference, grant agreement no. 834050) as well as the Institutional Strategy of the University of Tübingen (Deutsche Forschungsgemeinschaft, ZUK 63) and a RiSC grant by the MWK Baden-Württemberg.
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Blaschke, V., Daneyko, T., Kaparina, J., Gao, Z., Dellert, J. (2024). Navigable Atom-Rule Interactions in PSL Models Enhanced by Rule Verbalizations, with an Application to Etymological Inference. In: Muggleton, S.H., Tamaddoni-Nezhad, A. (eds) Inductive Logic Programming. ILP 2022. Lecture Notes in Computer Science(), vol 13779. Springer, Cham. https://doi.org/10.1007/978-3-031-55630-2_2
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