Going Dutch: Creating SimpleNLG-NL
By Ruud de Jong, Mariët Theune. 2018
11 citations recorded by the source corpus.
This paper presents SimpleNLG-NL, an adaptation of the SimpleNLG surface realisation engine for the Dutch language. It describes a novel method for determining and testing the grammatical constructions to be implemented, using target sentences sampled from a treebank.
Subfields: Artificial Intelligence, Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Filip Jurvc'ivcek
- Ondrej Dusek
- Verena Rieser
- Jekaterina Novikova
- Yevgeniy Puzikov
- Zdeněk Kasner
- Sebastian Gehrmann
- Ehud Reiter
In Natural Language Processing
- Filip Jurvc'ivcek
- Ondrej Dusek
- Verena Rieser
- Mihir Kale
- Jekaterina Novikova
- Abhinav Rastogi
- Yevgeniy Puzikov
- Zdeněk Kasner
Citations in the corpus
- Neural Generation for Czech: Data and Baselines (2019, background): “…procedural Sim-pleNLG realizer (Gatt and Reiter, 2009) has also been ported into multiple languages (Bollmann, 2011; Vaudry and Lapalme, 2013; de Oliveira and Sripada, 2014; Mazzei et al., 2016; Ramos-Soto et al., 2017; Cascallar-Fuentes et al., 2018; Chen et al., 2018; de Jong and Theune, 2018).”
- A Conversational (methodology): “In Dutch plural words generally end with “-s” or “-en” , if this is not the case, simpleNLG-NL [6] is used to inflect the word.”