*Research Institute in Information and Language Processing; University of Wolverhampton; MB Building, Stafford Street; Wolverhampton, WV1 1LY, UK; email@example.com
The annotation of temporal relations remains a challenge, being a very difﬁcult task for humans, not to mention machines, to reliably and consistently annotate temporal relations in natural language texts. This paper advocates a change in the deﬁnition of the problem itself, by proposing a staged divide-and-conquer approach guided by syntax, that offers a more principled way of selecting temporal entities involved in a temporal relation. The decomposition of the problem into smaller syntactically motivated tasks, and the identiﬁcation of accurate and linguistically grounded solutions to solve them, promote a sound understanding of the phenomena involved in establishing temporal relations. We illustrate the potential of linguistically informed solutions in the area of temporal relation identiﬁcation by proposing and evaluating an initial set of syntactically motivated tasks.