Entity Annotation based on Inverse Index Operations

Entity annotation involves attaching a label such as `name' or `organization' to a sequence of tokens in a document. All the current rule-based and machine learningbased approaches for this task operate at the document level. We present a new and generic approach to entity annotation which uses the inverse index typically created for rapid key-word based searching of a document collection. We define a set of operations on the inverse index that allows us to create annotations defined by cascading regular expressions. The entity annotations for an entire document corpus can be created purely of the index with no need to access the original documents. Experiments on two publicly available data sets show very significant performance improvements over the documentbased annotators.

• Type: Conference
• Year: 2006
• Where: EMNLP
• Authors: Ganesh Ramakrishnan, Sreeram Balakrishnan, Sachindra Joshi
• Keywords: Document, EMNLP 2006, EMNLP 2007, Entity Annotations, Inverse Index