The database creation utilized automated text processing tools that detect if
a news article contains a protest event, locate protest information within the
article, and extract pieces of information regarding the detected protest
events. The basis of training and testing the automated tools is the GLOCON
Gold Standard Corpus (GSC), which contains news articles from multiple sources
from each focus country. The articles in the GSC were manually coded by skilled
annotators in both classification and extraction tasks with the utmost accuracy
and consistency that automated tool development demands. In order to assure
these, the annotation manuals in this document lay out the rules according to
which annotators code the news articles. Annotators refer to the manuals at all
times for all annotation tasks and apply the rules that they contain. The
content of the annotation manual is built on the general principles and
standards of linguistic annotation laid out in other prominent annotation
manuals such as ACE, CAMEO, and TimeML. These principles, however, have been
adapted or rather modified heavily to accommodate the social scientific
concepts and variables employed in the EMW project. The manual has been molded
throughout a long trial and error process that accompanied the annotation of
the GSC. It owes much of its current shape to the meticulous work and
invaluable feedback provided by highly specialized teams of annotators, whose
diligence and expertise greatly increased the quality of the corpus.

使用自动化文本处理工具通过 GLOCON Gold Standard Corpus 进行训练和测试，开发并优化了可以检测新闻文章中的抗议事件、定位抗议信息并提取相关信息的工具，并根据注释手册中的规则为数据集进行手动编码。