Apportioning Development Effort in a Probabilistic LR Parsing System through Evaluation
<|reference_start|>Apportioning Development Effort in a Probabilistic LR Parsing System through Evaluation: We describe an implemented system for robust domain-independent syntactic parsing of English, using a unification-based grammar of part-of-speech and punctuation labels coupled with a probabilistic LR parser. We present evaluations of the system's performance along several different dimensions; these enable us to assess the contribution that each individual part is making to the success of the system as a whole, and thus prioritise the effort to be devoted to its further enhancement. Currently, the system is able to parse around 80% of sentences in a substantial corpus of general text containing a number of distinct genres. On a random sample of 250 such sentences the system has a mean crossing bracket rate of 0.71 and recall and precision of 83% and 84% respectively when evaluated against manually-disambiguated analyses.<|reference_end|>
@article{carroll1996apportioning,
    title={Apportioning Development Effort in a Probabilistic LR Parsing System
  through Evaluation},
    author={John Carroll (University of Sussex) and Ted Briscoe (University of
  Cambridge)},
    journal={Conference on Empirical Methods in Natural Language Processing
  (EMNLP-96), 92-100},
    year={1996},
    archivePrefix={arXiv},
    eprint={cmp-lg/9604004},
    primaryClass={cmp-lg cs.CL}
}