Linguistic realisation as machine translation: Comparing different MT models for AMR-to-text generation
Proceedings of the 10th International Conference on Natural Language …, 2017•aclanthology.org
In this paper, we study AMR-to-text generation, framing it as a translation task and
comparing two different MT approaches (Phrase-based and Neural MT). We systematically
study the effects of 3 AMR preprocessing steps (Delexicalisation, Compression, and
Linearisation) applied before the MT phase. Our results show that preprocessing indeed
helps, although the benefits differ for the two MT models.
comparing two different MT approaches (Phrase-based and Neural MT). We systematically
study the effects of 3 AMR preprocessing steps (Delexicalisation, Compression, and
Linearisation) applied before the MT phase. Our results show that preprocessing indeed
helps, although the benefits differ for the two MT models.
Abstract
In this paper, we study AMR-to-text generation, framing it as a translation task and comparing two different MT approaches (Phrase-based and Neural MT). We systematically study the effects of 3 AMR preprocessing steps (Delexicalisation, Compression, and Linearisation) applied before the MT phase. Our results show that preprocessing indeed helps, although the benefits differ for the two MT models.
aclanthology.org
以上显示的是最相近的搜索结果。 查看全部搜索结果