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Verb-sense Classifier

This system addresses the verb sense disambiguation (VSD) problem, a sub-problem of word sense disambiguation (WSD), for English. It predicts the sense that a verb features in a given sentence, from among other, potential different meanings.

This system was developed as a part of Semantic Role Labeling system.

Performance

Here is the performance of this system after the most recent training:

Label Correct Excess Missed Precision Recall F1
01 4230 205 113 95.38 97.4 96.38
02 378 88 147 81.12 72 76.29
03 178 30 60 85.58 74.79 79.82
04 51 16 14 76.12 78.46 77.27
05 16 10 16 61.54 50 55.17
06 10 8 10 55.56 50 52.63
07 3 2 3 60 50 54.55
08 6 4 0 60 100 75
09 3 2 3 60 50 54.55
10 0 3 3 0 0 0
11 10 1 0 90.91 100 95.24
12 3 1 3 75 50 60
13 1 2 1 33.33 50 40
14 5 1 3 83.33 62.5 71.43
15 0 2 0 0 0 0
16 0 1 0 0 0 0
17 1 1 0 50 100 66.67
18 0 1 0 0 0 0
19 0 0 1 0 0 0
20 0 0 1 0 0 0
All 4895 378 378 92.83 92.83 92.83

Usage

While you can dig through the code to use it directly, we suggest you use it through our pipeline. More details in pipeline's instructions.

Citation

If you use this system, and want to give credits to our system, please cite the following work:

@inproceedings{PRYZT04,
    author = {V. Punyakanok and D. Roth and W. Yih and D. Zimak and Y. Tu},
    title = {Semantic Role Labeling via Generalized Inference over Classifiers Shared Task Paper},
    booktitle = {CoNLL},
    pages = {130--133},
    year = {2004},
    comment = {Semantic Parsing; Structure Learning with Expressive Constraints; Constraint Optimization; Integer Linear Programming},
}