If it may have happened before, it happened, but not necessarily before

Authors:
Albert Gatt;François Portet
Affiliations:
University of Malta Tal-Qroqq, Msida, Malta;CNRS, Laboratoire d'Informatique de Grenoble, Grenoble, France
Venue:
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
Year:
2011

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Abstract

Temporal uncertainty in raw data can impede the inference of temporal and causal relationships between events and compromise the output of data-to-text NLG systems. In this paper, we introduce a framework to reason with and represent temporal uncertainty from the raw data to the generated text, in order to provide a faithful picture to the user of a particular situation. The model is grounded in experimental data from multiple languages, shedding light on the generality of the approach.