Logical Forms are an exceptionally important linguistic representation for highly demanding semantically related tasks like Question / Answering and Text Understanding, but their automatic production at runtime is higly error-prone. The use of a tool like XWNet and other similar resources would be beneficial for all the NLP community, but not only. The problem is: Logical Forms are useful as long as they are consistent, otherwise they would be useless if not harmful. Like any other resource that aims at providing a meaning representation, LFs require a big effort in manual checking order to reduce the number of errors to the minimum acceptable – less than 1 %- from any digital resource. As will be shown in detail in the paper, the available resources – XWNet, WN30-lfs, ILF-suffer from lack of a careful manual checking phase, and the number of errors is too high to make the resource usable as is. We classified mistakes by their syntactic or semantic type in order to facilitate a revision of the resource that we intend to do using regular expressions. We also commented extensively on semantic issues and on the best way to represent them in Logical Forms. 1.