# Reconstructing Maps from Text

arXiv: https://arxiv.org/abs/2005.08932 · HTML: https://mlsanity.com/paper/2005.08932/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 May 2020.

## Built on by (most cited first, 2 of 2)

- [Language with Vision: a Study on Grounded Word and Sentence Embeddings](https://mlsanity.com/paper/2206.08823/) (2022)
- [Language, Environment, and Robotic Navigation](https://mlsanity.com/paper/2404.03049/) (2024)

## Abstract (arXiv)

Previous research has demonstrated that Distributional Semantic Models (DSMs) are capable of reconstructing maps from news corpora (Louwerse & Zwaan, 2009) and novels (Louwerse & Benesh, 2012). The capacity for reproducing maps is surprising since DSMs notoriously lack perceptual grounding (De Vega et al., 2012). In this paper we investigate the statistical sources required in language to infer maps, and resulting constraints placed on mechanisms of semantic representation. Study 1 brings word co-occurrence under experimental control to demonstrate that direct co-occurrence in language is necessary for traditional DSMs to successfully reproduce maps. Study 2 presents an instance-based DSM that is capable of reconstructing maps independent of the frequency of co-occurrence of city names.