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Monotonic Inference with Unscoped Episodic Logical Forms: From Principles to System

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Abstract

We describe the foundations and the systematization of natural logic-like monotonic inference using unscoped episodic logical forms (ULFs) that as reported by Kim et al. (Proceedings of the 1st and 2nd Workshops on Natural Logic Meets Machine Learning (NALOMA), Groningen, 2021a, b) introduced and first evaluated. In addition to providing a more detailed explanation of the theory and system, we present results from extending the inference manager to address a few of the limitations that as reported by Kim et al. (Proceedings of the 1st and 2nd Workshops on Natural Logic Meets Machine Learning (NALOMA), Groningen, 2021b) naive system has. Namely, we add mechanisms to incorporate lexical information from the hypothesis (or goal) sentence, enable the inference manager to consider multiple possible scopings for a single sentence, and match against the goal using English rather than the ULF.

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Notes

  1. We use “goal-directed inference” here as an umbrella term for any inference method that uses knowledge of the goal in the search process.

  2. Some other notable variations of Natural Logic are described by Lavalle-Martínez et al. (2017).

  3. For the correspondence of these rules to Sánchez-Valencia’s (1991) natural logic, please see Kim et al.’s (2021a) explanation.

  4. The computation of global polarity via local entailment context propagation and irrelevant polarity marking symbols are omitted for brevity and clarity.

  5. The version 0.2.0 release and the benepar_en3 model available at https://github.com/nikitakit/self-attentive-parser/.

  6. The transduction rules are written in a combination of the tree-to-tree transduction language (Purtee & Schubert, 2012) and a simplified variant.

  7. This is available through the Natural Logic component of Stanford CoreNLP.

  8. For example, in positive contexts, the may be replaced with a, as in, I saw the dog \(\Rightarrow \) I saw a dog. The imposes a flat entailment context on its restrictor whereas a imposes a positive entailment context which warrants a fresh computation of the global polarity markings.

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Acknowledgements

This work was supported by NSF EAGER grant NSF IIS-1908595, DARPA CwC subcontract W911NF-15-1-0542, and a Sproull Graduate Fellowship from the University of Rochester.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of South Florida, 4202 E. Fowler Ave., Tampa, FL, 33620, USA

    Gene Louis Kim

  2. Department of Computer Science, Boston University, 665 Commonwealth Ave., Boston, MA, 02215, USA

    Mandar Juvekar

  3. Department of Computer Science, University of Rochester, 250 Hutchison Rd., Rochester, NY, 14627, USA

    Junis Ekmekciu & Lenhart Schubert

  4. Department of Computer Science, College of William & Mary, 251 Jamestown Rd., Williamsburg, VA, 23185, USA

    Viet Duong

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  1. Gene Louis Kim
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  5. Lenhart Schubert
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Correspondence to Gene Louis Kim.

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Kim, G.L., Juvekar, M., Ekmekciu, J. et al. Monotonic Inference with Unscoped Episodic Logical Forms: From Principles to System. J of Log Lang and Inf 33, 69–88 (2024). https://doi.org/10.1007/s10849-023-09412-2

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