A Deep Neural Network for Chinese Zero Pronoun Resolution
Table 2: Experimental results on the test data. ZPSNN represents our approach. †∗ indicate that our approach is statistical significant over the baseline system (using t-test, with p<0.05).
['[EMPTY]', 'Setting 1: Gold Parse + Gold AZP Baseline', 'Setting 1: Gold Parse + Gold AZP Baseline', 'Setting 1: Gold Parse + Gold AZP Baseline', 'Setting 1: Gold Parse + Gold AZP  [BOLD] ZPSNN', 'Setting 1: Gold Parse + Gold AZP  [BOLD] ZPSNN', 'Setting 1: Gold Parse + Gold AZP  [BOLD] ZPSNN', 'Setting 2: Gold Parse + System AZP Baseline', 'Setting 2: Gold Parse + System AZP Baseline', 'Setting 2: Gold Parse + System AZP Baseline', 'Setting 2: Gold Parse + System AZP  [BOLD] ZPSNN', 'Setting 2: Gold Parse + System AZP  [BOLD] ZPSNN', 'Setting 2: Gold Parse + System AZP  [BOLD] ZPSNN', 'Setting 3: System Parse + System AZP Baseline', 'Setting 3: System Parse + System AZP Baseline', 'Setting 3: System Parse + System AZP Baseline', 'Setting 3: System Parse + System AZP  [BOLD] ZPSNN†∗', 'Setting 3: System Parse + System AZP  [BOLD] ZPSNN†∗', 'Setting 3: System Parse + System AZP  [BOLD] ZPSNN†∗']
We employ \citeauthorchen2016 \shortcitechen2016’s system as the baseline, which is the state-of-the-art Chinese ZP resolution system. To evaluate our proposed approach, following \citeauthorchen2016 \shortcitechen2016, three experimental settings are designed. In Setting 1, we assume that gold AZPs and gold syntactic parse trees are available (obtained from the CoNLL-2012 shared task dataset). Finally, in Setting 3, we employ system AZP and system syntactic parse trees that obtained by Berkeley parser, which is the state-of-the-art parsing model. As we can see, our approach significantly outperforms the baseline system under three experimental settings by 1.4%, 1.9%, 2.5% in terms of overall F-score, respectively. In per-source results, for Setting 1 and 2, ZPSNN beats the baseline system in four of the six sources of data, especial on the source BC, which has the most AZPs in six sources. Moreover, in Setting 3, our system achieves higher performance than the baseline system in all the six sources of data. All these approve that our proposed approach achieves a considerable improvement in Chinese ZP resolution.