Factorising AMR generation through syntax
Table 2: Average number of acceptable realisations out of 3. The difference is significant with p<0.001.
['Model', '# good realisations']
We then crowdsourced acceptability judgments for each example from 100 annotators: we showed the reference realisation of an AMR graph, together with model realisations, and asked each annotator to mark all the grammatical realisations which have the same meaning as the reference realisation. Each annotator was presented 30 examples selected randomly. This shows the utility of separating out syntactic and lexical variation: we model explicitly meaning-preserving invariances, and can therefore generate better paraphrases.