Representations of Time Expressions for Temporal Relation Extraction with Convolutional Neural Networks

Lin C, Miller T, Dligach D, Bethard S, Savova G. Representations of Time Expressions for Temporal Relation Extraction with Convolutional Neural Networks. In: BioNLP 2017. Vancouver, Canada,: Association for Computational Linguistics; 2017. pp. 322–327.

Abstract

Token sequences are often used as the input for Convolutional Neural Networks (CNNs) in natural language processing. However, they might not be an ideal representation for time expressions, which are long, highly varied, and semantically complex. We describe a method for representing time expressions with single pseudo-tokens for CNNs. With this method, we establish a new state-of-the-art result for a clinical temporal relation extraction task.
Last updated on 02/25/2023