Consistency Queries in Information Extraction

Abstract

A new formal framework of learning - learning by consistency queries - is introduced and studied. The theoretical approach outlined here is implemented as the core technology of a prototypical development system named LExIKON which supports interactive information extraction in practically relevant cases exactly in the way described in the present paper. The overall scenario of learning by consistency queries for information extraction is formalized and different constraints on the query learners are discussed and formulated. The principle learning power of the resulting types of query learners is analyzed by comparing it to the power of well-known types of standard learning devices including unconstrained inductive inference machines as well as consistent, total, finite, and iterative learners.