Working with Web archives raises a number of issues caused by their temporal characteristics. Depending on the age of the content, additional knowledge might be needed to find and understand older texts. Especially facts about entities are subject to change. Most severe in terms of information retrieval are name changes. In order to find entities that have changed their name over time, search engines need to be aware of this evolution. We tackle this problem by analyzing Wikipedia in terms of entity evolutions mentioned in articles regardless the structural elements. We gathered statistics and automatically extracted minimum excerpts covering name changes by incorporating lists dedicated to that subject. In future work, these excerpts are going to be used to discover patterns and detect changes in other sources. In this work we investigate whether or not Wikipedia is a suitable source for extracting the required knowledge.
Most related to the long-term aim of this work, a knowledge base dedicated to entity evolution, is YAGO2 @cite_8 . It is an endeavor to extend the original YAGO knowledge base with temporal as well as spatial information. Most relevant to us is the temporal data, which YAGO2 incorporates to enhance entities as well as facts. In contrast to our aim, they do not gather this data by extracting new knowledge. Instead, they use temporal information which has already been extracted for YAGO and connect it to the corresponding entity or fact. For instance, date of birth and date of death are considered as a person's time of existence. Therefore, dates of name changes are still missing as they are not present in YAGO either.
@cite_8
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We present YAGO2, an extension of the YAGO knowledge base, in which entities, facts, and events are anchored in both time and space. YAGO2 is built automatically from Wikipedia, GeoNames, and WordNet. It contains 447 million facts about 9.8 million entities. Human evaluation confirmed an accuracy of 95 of the facts in YAGO2. In this paper, we present the extraction methodology, the integration of the spatio-temporal dimension, and our knowledge representation SPOTL, an extension of the original SPO-triple model to time and space.