Name ambiguity has long been viewed as a challenging problem in many applications, such as scientific literature management, people search, and social network analysis. When we search a person name in these systems, many documents (e.g., papers, webpages) containing that person’s name may be returned. Which documents are about the person we care about? Although much research has been conducted, the problem remains largely unsolved, especially with the rapid growth of the people information available on the Web. Content This data set contains 110 author names and their disambiguation results (ground truth). For each author, there are 3 json entries. The most important files are xxx_xml, xxx(classify)_txt, and xxx_txt. The xxx(classify)_txt contains the ground truth and the other two files (xxx_xml and xxx_txt) provide features to perform the disambiguation. At the high-level, the xxx_xml file includes title, venue, coauthor, affiliation, and the xxx.txt further contains citation, co-affiliation-occur and homepage. Let us use "Ajay Gupta" as the example to explain what information contained in each file. - Ajay Gupta.xml. The raw file. is formatted as a XML file. In the XML file, the author name is associated with a number of publications. An example of a publication is as follow: " " where