Memory-Based Shallow Parsing
| dc.creator | Daelemans, Walter | |
| dc.creator | Buchholz, Sabine | |
| dc.creator | Veenstra, Jorn | |
| dc.date | 1999-06-02 | |
| dc.date.accessioned | 2026-07-07T03:24:08Z | |
| dc.date.available | 2026-07-07T03:24:08Z | |
| dc.description | We present a memory-based learning (MBL) approach to shallow parsing in which POS tagging, chunking, and identification of syntactic relations are formulated as memory-based modules. The experiments reported in this paper show competitive results, the F-value for the Wall Street Journal (WSJ) treebank is: 93.8% for NP chunking, 94.7% for VP chunking, 77.1% for subject detection and 79.0% for object detection. | |
| dc.description | 8 pages, to appear in: Proceedings of the EACL'99 workshop on Computational Natural Language Learning (CoNLL-99), Bergen, Norway, June 1999 | |
| dc.identifier | https://arxiv.org/abs/cs/9906005 | |
| dc.identifier | http://arxiv.org/abs/cs/9906005 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/33209 | |
| dc.subject | Computation and Language | |
| dc.subject | Machine Learning | |
| dc.subject | I.6.2;I.7.1 | |
| dc.title | Memory-Based Shallow Parsing | |
| dc.type | text |