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篇名 漢文佛典的語意標記與應用:《高僧傳》文獻的時空資訊視覺化和語意搜尋
卷期 74
並列篇名 Semantic markup for Chinese Buddhist texts and its Application- A Platform for Querying and Spatio-temporal Visualization of the
作者 洪振洲馬德偉許智偉
頁次 001-024
關鍵字 佛教數位典藏語意標記地理資訊系統Buddhist digtal archivesSemantic markupGeographic information system
出刊日期 201008

中文摘要

《高僧傳》文獻的語意標記是在2008到2010年間,法鼓佛教學院於浩然基金會贊助下,所完成的數位文獻專案成果之一。此專案完成梁、唐、宋、明四本高僧傳,共一千三百多位的高僧傳記之內容語意標記。標記的內容除包括了文獻中所有的人物、地點、時間實體外,也包含三者交錯所形成的「關係點」。本專案完成的語意標記文獻,為目前所知最大量的以TEI標準完成之中文語意標記文庫。利用標記成果,我們得以使用特定的人物、時間或地點作為搜尋條件,來搜尋高僧傳的內容。並且透過線上介面,結合GIS 的技術應用,讓使用者體會到《高僧傳》不一樣的面向。

英文摘要

The construction of semantic markup for Biographies of Eminent Monks is part of a project on digital documents conducted at Dharma Drum Buddhist College between 2008 and 2010 with support from the Haoran Foundation. The achievement contributes to the field of digital humanities and electronic librarianship in several ways. To our knowledge, so far this construction has been the largest classical Chinese corpus with structural
and semantic markup in TEI. The four biographical collectionsrespectively from the Liang, Tang, Song, and Ming dynasty contain more than 1,300 biographies of the most famous figures in Chinese Buddhist history. By
applying semantic markup to the task of distinguishing and referencing all personal and place names as well as all dates in these texts, it is possible to present the texts in a much more user-friendly format. In this paper, we describe an approach to interface design based on semantic markup and inspired by GIS technology that maps the contents of the biographies in geographic space. The semantic markup allows us to search the dataset in ways that go far beyond available indexes. It is for the first time now possible to search e.g. for events at a certain period in a certain area. Another innovation is the concept of nexus point which describes basic events in the form “One or more person(s) at a certain time in a certain place.” With these nexus points expressed in
markup, we can display events in Chinese Buddhist history on a map and reference these visualizations directly back into the texts themselves.

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