Surface Realisation Using Full Delexicalisation

Anastasia Shimorina (1) , Claire Gardent (1)

1 SYNALP - Natural Language Processing : representations, inference and semantics

Surface realisation (SR) maps a meaning representation to a sentence and can be viewed as consisting of three subtasks: word ordering, morphological inflection and contraction generation (e.g., clitic attachment in Portuguese or elision in French). We propose a modular approach to surface realisation which models each of these components separately, and evaluate our approach on the 10 languages covered by the SR'18 Surface Realisation Shared Task shallow track. We provide a detailed evaluation of how word order, morphological realisa-tion and contractions are handled by the model and an analysis of the differences in word ordering performance across languages.

Domaines: Intelligence artificielle [cs.AI]

Anastasia Shimorina, Claire Gardent. Surface Realisation Using Full Delexicalisation. 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Nov 2019, Hong Kong, China. pp.3084-3094, ⟨10.18653/v1/D19-1305⟩. ⟨hal-02277069⟩