Name
Abstract | ||
|---|---|---|
In a recent article published in this journal (van Deemter, Gatt, van der Sluis, & Power, 2012), the authors criticize the Incremental Algorithm (a well-known algorithm for the generation of referring expressions due to Dale & Reiter, 1995, also in this journal) because of its strong reliance on a pre-determined, domain-dependent Preference Order. The authors argue that there are potentially many different Preference Orders that could be considered, while often no evidence is available to determine which is a good one. In this brief note, however, we suggest (based on a learning curve experiment) that finding a Preference Order for a new domain may not be so difficult after all, as long as one has access to a handful of human-produced descriptions collected in a semantically transparent way. We argue that this is due to the fact that it is both more important and less difficult to get a good ordering of the head than of the tail of a Preference Order. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1111/j.1551-6709.2012.01258.x | COGNITIVE SCIENCE |
Keywords | Field | DocType |
Generation,production of referring expressions,Evaluation metrics for generation algorithms,Incremental algorithm,Psycholinguistics,Reference,Learning curve experiments | Expression (mathematics),Computer science,Computational linguistics,Algorithm,Psycholinguistics | Journal |
Volume | Issue | ISSN |
36 | 5.0 | 0364-0213 |
Citations | PageRank | References |
2 | 0.39 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emiel Krahmer | 1 | 866 | 110.30 |
| Ruud Koolen | 2 | 34 | 8.88 |
| Mariët Theune | 3 | 379 | 43.91 |