Name
Abstract | ||
|---|---|---|
Events in text documents are interrelated in complex ways. In this paper, we study two types of relation: Event Coreference and Event Sequencing. We show that the popular tree-like decoding structure for automated Event Coreference is not suitable for Event Sequencing. To this end, we propose a graph-based decoding algorithm that is applicable to both tasks. The new decoding algorithm supports flexible feature sets for both tasks. Empirically, our event coreference system has achieved state-of-the-art performance on the TAC-KBP 2015 event coreference task and our event sequencing system beats a strong temporal-based, oracle-informed baseline. We discuss the challenges of studying these event relations. |
Year | Venue | Field |
|---|---|---|
2018 | COLING | Graph,Coreference,Computer science,Artificial intelligence,Natural language processing,Decoding methods,Machine learning |
DocType | Volume | Citations |
Conference | C18-1 | 0 |
PageRank | References | Authors |
0.34 | 23 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhengzhong Liu | 1 | 37 | 7.69 |
| Teruko Mitamura | 2 | 719 | 86.39 |
| Eduard H. Hovy | 3 | 7450 | 663.27 |