Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representations
Table 5: F-scores on the dev set for adding different ratios of CAMR and JAMR parsed AMRs to our initial data set. All scores are without postprocessing improvement methods.
['[BOLD] # CAMR AMRs', '[BOLD] # JAMR AMRs', '[BOLD] F-score']
We now have to determine which AMR to add to our silver data set. CAMR produces higher quality AMRs in general (64.0 vs 55.0 on the test set), but it might be beneficial to introduce some variety by also adding JAMR-parsed AMRs. We never add both CAMR and JAMR for the same sentence. We performed five experiments in which we added 100k silver AMRs, either containing 100%, 75%, 67%, 50% or 0% CAMR-parsed AMRs.