AI

Annotating Topic Development in Information Seeking Queries

Abstract

This paper contributes to the limited body of empirical research into the domain of discourse structure of information seeking queries. In this paper we describe the development of an annotation schema for coding topic development in information seeking queries and the initial observations from a pilot sample of query sessions. The main idea explored is the relationship between constant and variable discourse entities and their role in tracking changes in the topic progression. We argue that the topicalized entities remain stable across discourse moves and can be identified by a simple mechanism where anaphora resolution is a precursor. We also claim that a corpus annotated in this framework can be used as training data for dialogue management and computational semantics systems.