# Translating Place-Related Questions to GeoSPARQL Queries

arXiv: https://arxiv.org/abs/2205.03067 · HTML: https://mlsanity.com/paper/2205.03067/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 May 2022.

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

- [PolygonGNN: Representation Learning for Polygonal Geometries with Heterogeneous Visibility Graph](https://mlsanity.com/paper/2407.00742/) (2024)
- [Location Aware Modular Biencoder for Tourism Question Answering](https://mlsanity.com/paper/2401.02187/) (2024)
- [TerraQ: Spatiotemporal Question-Answering on Satellite Image Archives](https://mlsanity.com/paper/2502.04415/) (2025)

## Abstract (arXiv)

Many place-related questions can only be answered by complex spatial reasoning, a task poorly supported by factoid question retrieval. Such reasoning using combinations of spatial and non-spatial criteria pertinent to place-related questions is increasingly possible on linked data knowledge bases. Yet, to enable question answering based on linked knowledge bases, natural language questions must first be re-formulated as formal queries. Here, we first present an enhanced version of YAGO2geo, the geospatially-enabled variant of the YAGO2 knowledge base, by linking and adding more than one million places from OpenStreetMap data to YAGO2. We then propose a novel approach to translate the place-related questions into logical representations, theoretically grounded in the core concepts of spatial information. Next, we use a dynamic template-based approach to generate fully executable GeoSPARQL queries from the logical representations. We test our approach using the Geospatial Gold Standard dataset and report substantial improvements over existing methods.