Marquis: Generation of User-Tailored Multilingual Air Quality Bulletins

FootbOWL: Using a Generic Ontology of Football Competition for Planning Match Summaries

“…It consists of three tasks which are: mapping logico-semantic to discourse relations, determining discourse units, and discourse units ordering. As already pointed out in [20] (for a different domain), a logico-semantic relation can be mapped onto different discourse relations depending on the user's previous knowledge, the content being communicated and the information structure. In the current prototype, the mapping between logico-semantic and discourse relations is one-to-one.…”

“…4. The readability questionnaire put to the subjects is assessed or evaluated in order to produce new inferred knowledge that is more suitable for being communicated in natural language texts [16,20]. From the DBs/KBs, it is extracted for inclusion in schemas or discourse plan operators [9].…”

FORGe at SemEval-2017 Task 9: Deep sentence generation based on a sequence of graph transducers

“…1 It is built upon work presented, e.g., in (Bohnet, 2006;Wanner et al, 2010). It can be also considered an extended rule-based version of (Ballesteros et al, 2015).…”

Proceedings of the 15th European Workshop on Natural Language Generation (ENLG)

“…Some have suggested that causal relations also play an important role in improving narrative generation from real-life data Gervás, 2014). Several narrative generation systems already identify and make use of some causal relations (Hallett, 2008;Hunter et al, 2012;Bouayad-Agha et al, 2012;Wanner et al, 2010). Going one step further, Vaudry and Lapalme (2015) have raised the question of the possibility of extracting an appropriate causal network from real-life temporal data and use it to generate more coherent narratives.…”