Extractive email thread summarization: Can we do better than He Said She Said?
Pablo Ariel Duboue · 2012
Human-written, good quality extractive summaries pay great attention to the text intermixing the extracts. In this work, we focused on the lexical choice for verbs introducing quoted text. We analyzed 4000+ high quality summaries for a high traffic mailing list and manually assembled 39 quotation-introducing verb classes that cover the majority of the verb occurrences. A significant amount of the data is covered by on-going work on e-mail “speech acts. ” However, we found that one third of the “tail ” is composed by “risky ” verbs that most likely will be beyond the state of the art for longer time. We used this fact to highlight the trade-offs of risk taking in NLG, where interesting prose might come at the cost of unsettling some of the readers. 1