Work

Linguistic realisation as machine translation: Comparing different MT models for AMR-to-text generation

Year: 2017

Type: conference-paper

Abstract: In this paper, we study AMR-to-text generation, framing it as a translation task and comparing two different MT approaches (Phrasebased 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.The implementation of the models are publicly available 1 .

Source: International Conference on Natural Language Generation

DOI: 10.18653/v1/w17-3501

Authors: Thiago Castro Ferreira, Iacer Calixto, Sander Wubben, Emiel Krahmer

Institutions: Tilburg University, Dublin City University

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid