论文标题
基于模板的问题回答链接的地理空间数据
Template-Based Question Answering over Linked Geospatial Data
论文作者
论文摘要
最近在链接的开放数据云和许多国家制图机构的门户网站上提供了大量的地理空间数据（例如，OpenStreetMap数据，各个国家的行政地理位置或土地覆盖/土地使用数据集）。这些数据集使用各种地理空间词汇，可以使用SPARQL或其OGC标准的扩展GeoSparql查询。在本文中，我们超越了这些方法，在链接的地理空间数据源之上为自然语言问题提供了提问引擎。我们的系统已被实施，是Frankenstein问题回答体系结构的可重复使用的组件。我们使用一组201个自然语言问题进行了详细描述系统架构，其基本算法及其评估。一组问题作为研究社区作为黄金标准数据集提供，以对未来的地理空间问题回答引擎进行比较评估。
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.
