Virginia Francisco


Riddle Generation using Word Associations
Paloma Galván | Virginia Francisco | Raquel Hervás | Gonzalo Méndez
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In knowledge bases where concepts have associated properties, there is a large amount of comparative information that is implicitly encoded in the values of the properties these concepts share. Although there have been previous approaches to generating riddles, none of them seem to take advantage of structured information stored in knowledge bases such as Thesaurus Rex, which organizes concepts according to the fine grained ad-hoc categories they are placed into by speakers in everyday language, along with associated properties or modifiers. Taking advantage of these shared properties, we have developed a riddle generator that creates riddles about concepts represented as common nouns. The base of these riddles are comparisons between the target concept and other entities that share some of its properties. In this paper, we describe the process we have followed to generate the riddles starting from the target concept and we show the results of the first evaluation we have carried out to test the quality of the resulting riddles.


UCM-2: a Rule-Based Approach to Infer the Scope of Negation via Dependency Parsing
Miguel Ballesteros | Alberto Díaz | Virginia Francisco | Pablo Gervás | Jorge Carrillo de Albornoz | Laura Plaza
*SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012)