Grounding the ungrounded: Estimating locations of unknown place names from linguistic associations and grounded representations

Abstract Spatial locations can be extracted from language statistics, based on the idea that nearby locations are mentioned in similar linguistic contexts, akin to Tobler's first law of geography. However, the performance of language-based estimates is inferior to human estimates, raising questions about whether human spatial representations can actually be informed by such (inferior) statistics. We show that alternative methods of computing co-occurrence statistics improve language-based estimates, illustrating that simple linguistic