Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document Summarization
Table 4: Percentages of summary n-grams (or the entire sentences) appear in the multi-document input. (TAC-11)
['[BOLD] System', '[BOLD] 1-grams', '[BOLD] 2-grams', '[BOLD] 3-grams', '[BOLD] Sent']
Degree of extractiveness. PG-Original and PG-MMR summaries both show a high degree of extractiveness, and similar findings have been revealed by See et al. See et al. Because PG-MMR relies on a handful of representative source sentences and mutes the rest, it appears to be marginally more extractive than PG-Original. Both systems encourage generating summary sentences by stitching together source sentences, as about 52% and 41% of the summary sentences do not appear in the source, but about 90% the n-grams do.