Zero-shot Trajectory Mapping in Holocaust Testimonies

This work presents the task of Zero-shot Trajectory Mapping, which focuses on the spatial dimension of narratives. The task consists of two parts: (1) creating a “map” with all the locations mentioned in a set of texts, and (2) extracting a trajectory from a single testimony and positioning it within the map. Following recent advances in context length capabilities of large language models, we propose a pipeline for this task in a completely unsupervised manner, without the requirement of any type of labels. We demonstrate the pipeline on a set of ≈ 75 testimonies and present the resulting map and samples of the trajectory. We conclude that current long-range models succeed in generating meaningful maps and trajectories. Other than the visualization and indexing, we propose future directions for adaptation of the task as a step for dividing testimony sets into clusters and for alignment between parallel parts of different testimonies.