Translating Place-Related Questions to GeoSPARQL Queries

TL;DR

This paper enhances a geospatial knowledge base and introduces a novel translation method to convert natural language place-related questions into executable GeoSPARQL queries, enabling complex spatial reasoning on linked data.

Contribution

It presents an improved YAGO2geo knowledge base and a new translation approach for converting place questions into GeoSPARQL queries, grounded in spatial information theory.

Findings

Significant improvement over existing methods on the Geospatial Gold Standard dataset.

Enhanced YAGO2geo with over one million places from OpenStreetMap.

Effective translation of natural language questions into executable spatial queries.

Abstract

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.