Event Graph Schema Induction with Path Language Modeling
Event schemas can guide our understanding and ability to make predictions with respect to what might happen next. We propose a new Event Graph Schema, where two event types are connected through multiple paths involving entities that fill important roles in a coherent story.
Event Graph Schema Induction Task
- Input: Instance graphs contaning entities, relations, and events from input documents.
- Output: A set of recurring graph schemas from instance graphs. Figure 1 shows the example input and output of event graph schema induction.
This research is based upon work supported in part by U.S. DARPA KAIROS Program Nos. FA8750-19-2-1004, FA8750-19-2-0500 and FA8750-19-2-1003, U.S. DARPA AIDA Program No. FA8750-18-2-0014 and Air Force No. FA8650-17-C-7715. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of DARPA, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation therein.
Manling Li, Qi Zeng, Ying Lin, Kyunghyun Cho, Heng Ji, Jonathan May, Nathanael Chambers, Clare Voss. "Connecting the Dots: Event Graph Schema Induction with Path Language Modeling." In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 684-695. 2020.