Coherence in Natural Language: Data Structures and Applications
Florian Wolf, Edward GibsonA discussion of coherence in natural language that develops criteria for descriptively adequate data structures and examines the influence of coherence on psycholinguistic processes and determining the relative importance of document segments.
Wolf and Gibson evaluate whether tree structures are descriptively adequate for representing discourse coherence and conclude that more powerful data structure is needed because there are many different kinds of crossed dependencies and nodes with multiple parents in the discourse structures of naturally occurring texts. They propose that connected, labeled chain graphs make a better representation of coherence. They find additionally that causal coherence relations affect people's strategies for pronoun processing, which points to the psychological validity of coherence relations. Finally, they evaluate word-based, layout-based, and coherence-based approaches for estimating the importance of document segments in a document and find that coherence-based methods that operate on chain graphs perform best. With its attention to empirical validation and psycholinguistic processing, the book raises issues that are relevant to cognitive science as well as natural language processing and information extraction.