From Language to Time: A Temporal Expression Anchorer

Understanding temporal expressions in natural language is a key step towards incorporating temporal information in many applications. In this paper we describe a system capable of anchoring such expressions in English: system TEA features a constraint-based calendar model and a compact representational language to capture the intensional meaning of temporal expressions. We also report favorable results from experiments conducted on several email datasets.