In our work, we are interested in facilitating the exploration by scholars of the geography of texts: in particular, historical narrative texts describing routes. Semantic annotation constitutes the first step to enrich such text with the necessary information for producing analytical maps. The present article focuses on the disambiguation of spatial named entities (SNE) by the attribution of an identifier of the ever-growing Web of Data. This giant knowledge base (KB) provides qualitative spatial information about geographic entities, in particular spatial relations such as (:Paris :southOf :Lille), (:Paris :country :France). We thus propose a graph-matching algorithm relying on the A* algorithm and graph-edit distances for choosing the best referent in the KB for the SNE. We performed preliminary experiments and noted the clear gain in performance. We propose some examples of maps that are built semi-automatically. Finally, we draw conclusions and describe our plans of future work.

中文翻译：

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将空间命名实体链接到数据网以对历史文本进行地理分析

在我们的工作中，我们有兴趣促进学者对文本地理学的探索：特别是描述路线的历史叙事文本。语义注释构成了将此类文本与生成分析图所需的信息相结合的第一步。本文着重于通过不断增长的Web数据标识符的归属来消除空间命名实体（SNE）的歧义。这个巨大的知识库（KB）提供有关地理实体的定性空间信息，尤其是诸如（：Paris：southOf：Lille），（：Paris：country：France）的空间关系。因此，我们提出了一种基于A *算法和图编辑距离的图匹配算法，以为SNE选择KB中的最佳参考对象。我们进行了初步实验，并注意到性能明显提高。我们提出了一些半自动生成的地图示例。最后，我们得出结论并描述我们的未来工作计划。