Sergios-Anestis Kefalidis , Dharmen Punjani , Eleni Tsalapati , Konstantinos Plas , Maria-Aggeliki Pollali , Pierre Maret , Manolis Koubarakis
{"title":"The question answering system GeoQA2 and a new benchmark for its evaluation","authors":"Sergios-Anestis Kefalidis , Dharmen Punjani , Eleni Tsalapati , Konstantinos Plas , Maria-Aggeliki Pollali , Pierre Maret , Manolis Koubarakis","doi":"10.1016/j.jag.2024.104203","DOIUrl":null,"url":null,"abstract":"<div><div>We present the question answering engine GeoQA2 which is able to answer geospatial questions over the union of knowledge graphs YAGO2 and YAGO2geo. We also present the dataset <span>GeoQuestions1089</span> which consists of 1089 natural language questions, their corresponding SPARQL or GeoSPARQL queries and their answers over the union of the same knowledge graphs. We use this dataset to compare the effectiveness of GeoQA2 and the system of Hamzei et al. 2022 and make it publicly available to be used by other researchers. Our evaluation shows that although the engine GeoQA2 performs better than the engine of Hamzei et al. 2022, both engines have ample room for improvement in their question answering performance.</div></div>","PeriodicalId":73423,"journal":{"name":"International journal of applied earth observation and geoinformation : ITC journal","volume":"134 ","pages":"Article 104203"},"PeriodicalIF":7.6000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of applied earth observation and geoinformation : ITC journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569843224005594","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
We present the question answering engine GeoQA2 which is able to answer geospatial questions over the union of knowledge graphs YAGO2 and YAGO2geo. We also present the dataset GeoQuestions1089 which consists of 1089 natural language questions, their corresponding SPARQL or GeoSPARQL queries and their answers over the union of the same knowledge graphs. We use this dataset to compare the effectiveness of GeoQA2 and the system of Hamzei et al. 2022 and make it publicly available to be used by other researchers. Our evaluation shows that although the engine GeoQA2 performs better than the engine of Hamzei et al. 2022, both engines have ample room for improvement in their question answering performance.
期刊介绍：
The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
