Template-Based Question Answering over Linked Geospatial Data
Abstract
Large amounts of geospatial data have been made available recently on the linked open data cloud and the portals of many national cartographic agencies (e.g., OpenStreetMap data, administrative geographies of various countries, or land cover/land use data sets). These datasets use various geospatial vocabularies and can be queried using SPARQL or its OGC-standardized extension GeoSPARQL. In this paper, we go beyond these approaches to offer a question-answering engine for natural language questions on top of linked geospatial data sources. Our system has been implemented as re-usable components of the Frankenstein question answering architecture. We give a detailed description of the system's architecture, its underlying algorithms, and its evaluation using a set of 201 natural language questions. The set of questions is offered to the research community as a gold standard dataset for the comparative evaluation of future geospatial question answering engines.
Cite
@article{arxiv.2007.07060,
title = {Template-Based Question Answering over Linked Geospatial Data},
author = {Dharmen Punjani and Markos Iliakis and Theodoros Stefou and Kuldeep Singh and Andreas Both and Manolis Koubarakis and Iosif Angelidis and Konstantina Bereta and Themis Beris and Dimitris Bilidas and Theofilos Ioannidis and Nikolaos Karalis and Christoph Lange and Despina-Athanasia Pantazi and Christos Papaloukas and Georgios Stamoulis},
journal= {arXiv preprint arXiv:2007.07060},
year = {2021}
}
Comments
27 pages, 2 figures