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UCL+Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound
2016
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)
We develop a novel transition-based parsing algorithm for the abstract meaning representation parsing task using exact imitation learning, in which the parser learns a statistical model by imitating the actions of an expert on the training data. We then use the imitation learning algorithm DAGGER to improve the performance, and apply an α-bound as a simple noise reduction technique. Our performance on the test set was 60% in F-score, and the performance gains on the development set due to
doi:10.18653/v1/s16-1180
dblp:conf/semeval/GoodmanVN16
fatcat:n723tmnijzbfrjwccjtdowbhwq