@InProceedings{burek_pietsch_deroeck07:lsa_rte3,
  author =	 {Gaston Burek and Christian Pietsch and Anne De
                  Roeck},
  title =	 {{SVO triple based Latent Semantic Analysis for
                  recognising textual entailment}},
  booktitle =	 {Proceedings of the ACL-PASCAL Workshop on Textual
                  Entailment and Paraphrasing (WTEP) of the 45th
                  Annual Meeting of the Association of Computational
                  Linguistics (ACL 2007)},
  publisher =	 {Association for Computational Linguistics},
  year =	 2007,
  month =	 {June},
  address =	 {Prague, Czech Republic},
  pages =	 {113--118},
  annote =	 {Latent Semantic Analysis has only recently been
                  applied to textual entailment recognition. However,
                  these efforts have suffered from inadequate bag of
                  words vector representations. Our prototype
                  implementation for the Third Recognising Textual
                  Entailment Challenge (RTE-3) improves the approach
                  by applying it to vector representations that
                  contain semi-structured representations of words. It
                  uses variable size n-grams of word stems to model
                  independently verbs, subjects and objects displayed
                  in textual statements. The system performance shows
                  positive results and provides insights about how to
                  improve them further.},
  url =		 {http://www.aclweb.org/anthology/W/W07/W07-1419}
}