@inproceedings{lawley-etal-2021-learning,
title = "Learning General Event Schemas with Episodic Logic",
author = "Lawley, Lane and
Kuehnert, Benjamin and
Schubert, Lenhart",
editor = "Kalouli, Aikaterini-Lida and
Moss, Lawrence S.",
booktitle = "Proceedings of the 1st and 2nd Workshops on Natural Logic Meets Machine Learning (NALOMA)",
month = jun,
year = "2021",
address = "Groningen, the Netherlands (online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.naloma-1.1",
pages = "1--6",
abstract = "We present a system for learning generalized, stereotypical patterns of events{---}or {``}schemas{''}{---}from natural language stories, and applying them to make predictions about other stories. Our schemas are represented with Episodic Logic, a logical form that closely mirrors natural language. By beginning with a {``}head start{''} set of protoschemas{---} schemas that a 1- or 2-year-old child would likely know{---}we can obtain useful, general world knowledge with very few story examples{---}often only one or two. Learned schemas can be combined into more complex, composite schemas, and used to make predictions in other stories where only partial information is available.",
}
Markdown (Informal)
[Learning General Event Schemas with Episodic Logic](https://aclanthology.org/2021.naloma-1.1) (Lawley et al., NALOMA 2021)
ACL
- Lane Lawley, Benjamin Kuehnert, and Lenhart Schubert. 2021. Learning General Event Schemas with Episodic Logic. In Proceedings of the 1st and 2nd Workshops on Natural Logic Meets Machine Learning (NALOMA), pages 1–6, Groningen, the Netherlands (online). Association for Computational Linguistics.