Name
Abstract | ||
|---|---|---|
Script knowledge plays a central role in text understanding and is relevant for a variety of downstream tasks. In this paper, we consider two recent datasets which provide a rich and general representation of script events in terms of paraphrase sets. We introduce the task of mapping event mentions in narrative texts to such script event types, and present a model for this task that exploits rich linguistic representations as well as information on temporal ordering. The results of our experiments demonstrate that this complex task is indeed feasible. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.18653/v1/S17-1016 | *SEM |
DocType | Volume | Citations |
Journal | abs/1710.05709 | 0 |
PageRank | References | Authors |
0.34 | 13 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| simon ostermann | 1 | 17 | 2.81 |
| Michael Roth | 2 | 67 | 6.43 |
| Stefan Thater | 3 | 756 | 38.54 |
| Manfred Pinkal | 4 | 1116 | 69.77 |