Comparing two trainable grammatical relations finders
| dc.creator | Yeh, Alexander | |
| dc.date | 2000-08-08 | |
| dc.date.accessioned | 2026-07-07T03:16:26Z | |
| dc.date.available | 2026-07-07T03:16:26Z | |
| dc.description | Grammatical relationships (GRs) form an important level of natural language processing, but different sets of GRs are useful for different purposes. Therefore, one may often only have time to obtain a small training corpus with the desired GR annotations. On such a small training corpus, we compare two systems. They use different learning techniques, but we find that this difference by itself only has a minor effect. A larger factor is that in English, a different GR length measure appears better suited for finding simple argument GRs than for finding modifier GRs. We also find that partitioning the data may help memory-based learning. | |
| dc.description | 5 pages, uses colacl.sty | |
| dc.identifier | https://arxiv.org/abs/cs/0008004 | |
| dc.identifier | http://arxiv.org/abs/cs/0008004 | |
| dc.identifier | 18th International Conference on Computational Linguistics (COLING 2000), pages 1146-1150, Saarbruecken, Germany, July, 2000 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/30352 | |
| dc.subject | Computation and Language | |
| dc.subject | I.2.7 | |
| dc.title | Comparing two trainable grammatical relations finders | |
| dc.type | text |