We propose a morphology-based method for low-resource (LR) dependency parsing. We train a morphological inflector for target LR languages, and apply it to related rich-resource (RR) treebanks to create cross-lingual (x-inflected) treebanks that resemble the target LR language. We use such inflected treebanks to train parsers in zero- (training on x-inflected treebanks) and few-shot (training on x-inflected and target language treebanks) setups. The results show that the method sometimes improves the baselines, but not consistently.

翻译：我们为低资源(LR)依赖性分析提出了基于形态的方法。 我们为目标(LR)语言培训了一种形态学反射器,并将其应用到相关的富有资源(RR)树库中,以创建与目标(LR)语言相似的跨语言(x)树库。 我们用这种偏向型树库来培训零(对x偏向型树库的培训)和少见型(对x偏向型和目标语言树库的培训 ) 。 结果显示,这种方法有时可以改善基线,但并不一致。