Historical uncertainty in Gregory of Tours's History of the Franks (book 7)

Our goal was to create a research dataset based on geographical and chronological uncertainties in the work of Gregory of Tours's *History of the Franks* (book 7). We used and modified a topology of geographical and chronological uncertainty based on a rudimentary schema that would be universal when analysing an historical source : Chronological :<br> * uncertain dating<br> * uncertain method of dating<br> * lack of dating<br> * precise dating Geographical: <br> * uncertain location<br> * general location (region, country)<br> * lack of location <br> * precise location After working on book 7 for a while, that schema was reworked as those 9 types of uncertainty : Chronological :<br> * uncertain_dating<br> * uncertain_method_dating<br> * event_dating_null<br> * precise_dating Geographical: <br> * uncertain_location<br> * general_location <br> * event_location_null<br> * uncertain_method_location<br> * precise_location <br> The geographical and chronological focus makes it possible to identify where and when, in a source, the historical uncertainty is higher. Using python, that dataset was then automatically cleaned and enhanced with bounding box based on geo-mapping information for the entries of geographical uncertainty. Those were classified as either precise_location or general_location. For example, anything relating to a city general area (like "in the Rouen area") creates a general_location bounding box encompassing the *current* geographical space occupied by the municipality of Rouen (in the format 'LongMin', 'LongMax', 'LatMin', 'LatMax' in a single column "bbox"). Anything described as a unique point in space (like "in Paris") creates a precise_location and its corresponding lat/long system of coordinates. This is an arbitrary way to translate slightly undefined geographical concepts of uncertainty into formal data, but at least it can be fully explained explicitly.<br> Translation used: Tours G. <em>et alii</em>, <em>The history of the franks</em>, Penguin Books Limited, 1974, https://books.google.ch/books?id=4Lx-M2RHGgoC.本研究旨在基于都尔的格雷戈里（Gregory of Tours）所著*法兰克人史*（*History of the Franks*）第七卷中的地理与时间不确定性，构建科研数据集。我们基于一套用于历史史料分析的通用基础框架，复用并修改了地理与时间不确定性的分类体系，该体系最初包含以下类别： 时间维度： * 年代不确定 * 定年方法不确定 * 未标注年代 * 精确年代 地理维度： * 位置不确定 * 大致位置（区域、国家） * 未标注位置 * 精确位置 在针对第七卷开展一段时间的研究后，该框架被修订为以下9类不确定性： 时间维度： * 年代不确定（uncertain_dating） * 定年方法不确定（uncertain_method_dating） * 无年代标注（event_dating_null） * 精确年代（precise_dating） 地理维度： * 位置不确定（uncertain_location） * 大致位置（general_location） * 无位置标注（event_location_null） * 定位方法不确定（uncertain_method_location） * 精确位置（precise_location） 该时空聚焦的研究框架可用于识别史料中历史不确定性较高的时空节点。本研究借助Python语言对该数据集进行自动化清洗，并基于地理映射信息为地理不确定性条目添加边界框（bounding box）标注。上述地理不确定性条目被划分为精确位置（precise_location）与大致位置（general_location）两类。 例如，凡涉及城市周边区域的条目（如“鲁昂周边”），将被标注为大致位置边界框，其范围涵盖鲁昂市当前的行政辖区空间，边界框以单列`bbox`存储，格式为`LongMin`、`LongMax`、`LatMin`、`LatMax`。若条目描述为唯一空间点位（如“在巴黎”），则将其标注为精确位置，并附带对应的经纬度坐标系统。该方法将带有不确定性的模糊地理概念转化为结构化数据的方式具有一定主观性，但至少可实现完整的显性说明。 所用译本：都尔的格雷戈里等（Tours G. *et alii*），*法兰克人史*（*The History of the Franks*），企鹅图书有限公司（Penguin Books Limited），1974年，https://books.google.ch/books?id=4Lx-M2RHGgoC.