Memory-Based Shallow Parsing
<|reference_start|>Memory-Based Shallow Parsing: 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.<|reference_end|>
@article{daelemans1999memory-based,
    title={Memory-Based Shallow Parsing},
    author={Walter Daelemans, Sabine Buchholz, Jorn Veenstra},
    journal={arXiv preprint arXiv:cs/9906005},
    year={1999},
    number={ILK-9907},
    archivePrefix={arXiv},
    eprint={cs/9906005},
    primaryClass={cs.CL cs.LG}
}