Paper: Extractive email thread summarization: Can we do better than He Said She Said?

ACL ID W12-1513
Title Extractive email thread summarization: Can we do better than He Said She Said?
Venue International Conference on Natural Language Generation
Session Main Conference
Year 2012
Authors

Human-written, good quality extractive sum- maries pay great attention to the text intermix- ing the extracts. In this work, we focused on the lexical choice for verbs introducing quoted text. We analyzed 4000+ high quality sum- maries for a high traffic mailing list and manu- ally assembled 39 quotation-introducing verb classes that cover the majority of the verb oc- currences. 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 inter- esting prose might come at the cost of unset- tling some of the readers.