  The traditional entity extraction problem lies in the ability of extracting
named entities from plain text using natural language processing techniques and
intensive training from large document collections. Examples of named entities
include organisations, people, locations, or dates. There are many research
activities involving named entities; we are interested in entity ranking in the
field of information retrieval. In this paper, we describe our approach to
identifying and ranking entities from the INEX Wikipedia document collection.
Wikipedia offers a number of interesting features for entity identification and
ranking that we first introduce. We then describe the principles and the
architecture of our entity ranking system, and introduce our methodology for
evaluation. Our preliminary results show that the use of categories and the
link structure of Wikipedia, together with entity examples, can significantly
improve retrieval effectiveness.
