TY - JOUR T1 - Multiple alternative sentence compressions and word-pair antonymy for automatic text summarization and recognizing textual entailment JF - Proceedings of the Text Analysis Conference (TAC-2008), Gaithersburg, MD Y1 - 2008 A1 - Mohammad,S. A1 - Dorr, Bonnie J A1 - Egan,M. A1 - Jimmy Lin A1 - Zajic, David AB - The University of Maryland participatedin three tasks organized by the Text Anal- ysis Conference 2008 (TAC 2008): (1) the update task of text summarization; (2) the opinion task of text summariza- tion; and (3) recognizing textual entail- ment (RTE). At the heart of our summa- rization system is Trimmer, which gener- ates multiple alternative compressed ver- sions of the source sentences that act as candidate sentences for inclusion in the summary. For the first time, we investi- gated the use of automatically generated antonym pairs for both text summariza- tion and recognizing textual entailment. We used an antonymy feature in both the opinion summarization task and for rec- ognizing textual entailment. More coher- ent summaries resulted when using the antonymy feature as compared to when not using it. However, performance on ROUGE dropped. The RTE system per- formed almost equally well when using antonyms from WordNet and when using automatically generated antonyms. ER -