Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation
Table 4: Results on question sentences (§5.3). All of baseline C&C, EasySRL and depccg parsers are retrained on Questions data.
['Method', 'P', 'R', 'F1']
Contrary to our expectation, the plain depccg retrained on Questions data performs the best, with neither ELMo nor the proposed method taking any effect. We hypothesize that, since the evaluation set contains sentences with similar constructions, the contributions of the latter two methods are less observable on top of Questions data. Inspection of the output trees reveals that this is actually the case; the majority of differences among parser ’s configurations are irrelevant to question constructions, suggesting that the models capture well the syntax of question in the data.