# Generating Simulations of Motion Events from Verbal Descriptions

arXiv: https://arxiv.org/abs/1610.01713 · HTML: https://mlsanity.com/paper/1610.01713/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Oct 2016.

## Built on by (most cited first, 3 of 3)

- [Pretraining on Interactions for Learning Grounded Affordance Representations](https://mlsanity.com/paper/2207.02272/) (2022)
- [Do Trajectories Encode Verb Meaning?](https://mlsanity.com/paper/2206.11953/) (2022)
- [Comparing Trajectory and Vision Modalities for Verb Representation](https://mlsanity.com/paper/2303.12737/) (2023)

## Abstract (arXiv)

In this paper, we describe a computational model for motion events in natural language that maps from linguistic expressions, through a dynamic event interpretation, into three-dimensional temporal simulations in a model. Starting with the model from (Pustejovsky and Moszkowicz, 2011), we analyze motion events using temporally-traced Labelled Transition Systems. We model the distinction between path- and manner-motion in an operational semantics, and further distinguish different types of manner-of-motion verbs in terms of the mereo-topological relations that hold throughout the process of movement. From these representations, we generate minimal models, which are realized as three-dimensional simulations in software developed with the game engine, Unity. The generated simulations act as a conceptual "debugger" for the semantics of different motion verbs: that is, by testing for consistency and informativeness in the model, simulations expose the presuppositions associated with linguistic expressions and their compositions. Because the model generation component is still incomplete, this paper focuses on an implementation which maps directly from linguistic interpretations into the Unity code snippets that create the simulations.