Entity disambiguation is the problem of determining whether two mentions of entities refer to the same object: e.g., trying to decide whether the entity called “Jim Clark” in one document is the same as the entity called “Jim Clark” in another document. To do this accurately, it is necessary to extract from these documents descriptions of these entities as exhaustive and accurate as possible. This in turn requires ‘tracking’ these entities in each document – identifying all or most of their mentions – and collecting their properties, particularily those that help the most to discriminate between individuals.

The goal of the workshop is to further the state of the art in entity disambiguation by developing better techniques for tracking entities and for extracting their properties. A particular focus will be improving entity tracking by using lexical and encyclopedic knowledge extracted both from structured lexical databases and from semi-strcutured repositories such as Wikipedia. Lack of such knowledge is one of the main problems with current entity tracking methods, which typically cannot detect that ‘the Packwood proposal’ and ‘the Packwood plan’ in the following example refer to the same entity.

• [The Packwood proposal] would reduce the tax depending on how long an asset was held. It also would create a new IRA that would shield from taxation the appreciation on investments made for a wide variety of purposes, including retirement, medical expenses, first-home purchases and tuition.
• A White House spokesman said President Bush is “generally supportive” of [the Packwood plan]

Methods to be used include text mining techniques (supervised and unsupervised) to extract object properties; better machine learning techniques to improve entity tracking (e.g., using tree kernels); methods for extracting knowledge from WordNet, semantic role labellers, and Wikipedia; and clustering methods for entity disambiguation.

ELERFED CDC Overview
Entity Disambiguation Scoring Metrics
SVMs and Kernels
Wiki
Full CDED
Slides
Introduction
Slides
Versley System – PDF