Where Do We Go from Here? Multi-scale Allocentric Relational Inference from Natural Spatial Descriptions

Tzuf Paz-Argaman, Sayali Kulkarni, John Palowitch, Jason Baldridge, Reut Tsarfaty

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

When communicating routes in natural language, the concept of acquired spatial knowledge is crucial for geographic information retrieval (GIR) and in spatial cognitive research. However, NLP navigation studies often overlook the impact of such acquired knowledge on textual descriptions. Current navigation studies concentrate on egocentric local descriptions (e.g., 'it will be on your right') that require reasoning over the agent's local perception. These instructions are typically given as a sequence of steps, with each action-step explicitly mentioning and being followed by a landmark that the agent can use to verify they are on the right path (e.g., 'turn right and then you will see...'). In contrast, descriptions based on knowledge acquired through a map provide a complete view of the environment and capture its overall structure. These instructions (e.g., 'it is south of Central Park and a block north of a police station') are typically non-sequential, contain allocentric relations, with multiple spatial relations and implicit actions, without any explicit verification. This paper introduces the Rendezvous (RVS) task and dataset, which includes 10, 404 examples of English geospatial instructions for reaching a target location using map-knowledge. Our analysis reveals that RVS exhibits a richer use of spatial allocentric relations, and requires resolving more spatial relations simultaneously compared to previous text-based navigation benchmarks.

Original languageEnglish
Title of host publicationEACL 2024 - 18th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference
EditorsYvette Graham, Matthew Purver, Matthew Purver
PublisherAssociation for Computational Linguistics (ACL)
Pages1026-1040
Number of pages15
ISBN (Electronic)9798891760882
StatePublished - 2024
Event18th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2024 - St. Julian�s, Malta
Duration: 17 Mar 202422 Mar 2024

Publication series

NameEACL 2024 - 18th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference
Volume1

Conference

Conference18th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2024
Country/TerritoryMalta
CitySt. Julian�s
Period17/03/2422/03/24

Bibliographical note

Publisher Copyright:
© 2024 Association for Computational Linguistics.

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