Embedding Time Expressions for Deep Temporal Ordering Models
ACL (1), pp. 4400-4406, 2019.
Data-driven models have demonstrated state-of-the-art performance in inferring the temporal ordering of events in text. However, these models often overlook explicit temporal signals, such as dates and time windows. Rule-based methods can be used to identify the temporal links between these time expressions (timexes), but they fail to c...More
PPT (Upload PPT)