While the plan generation stage is guaranteed to be faithful to the input, the translation process from plans to text is based on a neural seq2seq model and may suffer from known issues with such models: hallucinating facts that do not exist in the input, repeating facts, or dropping facts. While the clear mapping between plans and text helps to reduce these issues greatly, the system in BIBREF0 still has 2% errors of these kinds. Recent work in neural text generation and summarization attempt to address these issues by trying to map the textual outputs back to structured predicates, and comparing these predicates to the input data. 
 Question: What is the effectiveness plan generation?
clear mapping between plans and text helps to reduce these issues greatly, the system in BIBREF0 still has 2% errors work in neural text generation and summarization attempt to address these issues