Prior-informed Distant Supervision for Temporal Evidence Classification
Ridho Reinanda, Maarten de Rijke, J. Tsujii, J. Hajič · UvA-DARE (University of Amsterdam) · 2014
Temporal evidence classification, i.e., finding associations between temporal expressions and re-lations expressed in text, is an important part of temporal relation extraction. To capture the variations found in this setting, we employ a distant supervision approach, modeling the task as multi-class text classification. There are two main challenges with distant supervision: (1) noise generated by incorrect heuristic labeling, and (2) distribution mismatch between the target and distant supervision examples. We are particularly interested in addressing the second problem and propose a sampling approach to handle the distribution mismatch. Our prior-informed distant supervision approach improves over basic distant supervision and outperforms a purely super-vised approach when evaluated on TAC-KBP data, both on classification and end-to-end metrics. 1