Simple is best: experiments with different document segmentation strategies for passage retrieval

Passage retrieval is used in QA to filter large document collections in order to find text units relevant for answering given questions. In our QA system we apply standard IR techniques and index-time passaging in the retrieval component. In this paper we investigate several ways of dividing documents into passages. In particular we look at semantically motivated approaches (using coreference chains and discourse clues) compared with simple window-based techniques. We evaluate retrieval performance and the overall QA performance in order to study the impact of the different segmentation approaches. From our experiments we can conclude that the simple techniques using fixed-sized windows clearly outperform the semantically motivated approaches, which indicates that uniformity in size seems to be more important than semantic coherence in our setup.