Article Dans Une Revue Journal of Artificial Intelligence Research Année : 2011

Evaluating Temporal Graphs Built from Texts via Transitive Reduction

Résumé

Temporal information has been the focus of recent attention in information extraction, leading to some standardization effort, in particular for the task of relating events in a text. This task raises the problem of comparing two annotations of a given text, because relations between events in a story are intrinsically interdependent and cannot be evaluated separately. A proper evaluation measure is also crucial in the context of a machine learning approach to the problem. Finding a common comparison referent at the text level is not obvious, and we argue here in favor of a shift from event-based measures to measures on a unique textual object, a minimal underlying temporal graph, or more formally the transitive reduction of the graph of relations between event boundaries. We support it by an investigation of its properties on synthetic data and on a well-know temporal corpus.

Dates et versions

inria-00602459 , version 1 (22-06-2011)

Identifiants

Citer

Xavier Tannier, Philippe Muller. Evaluating Temporal Graphs Built from Texts via Transitive Reduction. Journal of Artificial Intelligence Research, 2011, 40, pp.375--413. ⟨10.1613/jair.3118⟩. ⟨inria-00602459⟩
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