paper-with-me

Papers

Going Dutch: Creating SimpleNLG-NL

2018-11-01 · WS 2018 11 · Ruud de Jong, Mari{\"e}t Theune

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.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Text Generation

Similar Papers 제목 키워드 기반

SimpleNLG-DE: Adapting SimpleNLG 4 to German

2019-10-01 · WS 2019 10 · Daniel Braun, Kira Klimt, Daniela Schneider, Florian Matthes

SimpleNLG is a popular open source surface realiser for the English language. For German, however, the availability of open source and non-domain specific realisers is sparse, partly due to the complexity of the German l…

Adapting SimpleNLG to Galician language

2018-11-01 · WS 2018 11 · Andrea Cascallar-Fuentes, Alej Ramos-Soto, ro, Alberto Bugar{\'\i}n Diz

In this paper, we describe SimpleNLG-GL, an adaptation of the linguistic realisation SimpleNLG library for the Galician language. This implementation is derived from SimpleNLG-ES, the English-Spanish version of this libr…

Text Generation

SimpleNLG-TI: Adapting SimpleNLG to Tibetan

2020-12-01 · INLG (ACL) 2020 12 · Zewang Kuanzhuo, Li Lin, Zhao Weina

Surface realisation is the last but not the least phase of Natural Language Generation, which aims to produce high-quality natural language text based on meaning representations. In this article, we present our work on S…

Text Generation

SimpleNLG-ZH: a Linguistic Realisation Engine for Mandarin

2018-11-01 · WS 2018 11 · Guanyi Chen, Kees Van Deemter, Chenghua Lin

We introduce SimpleNLG-ZH, a realisation engine for Mandarin that follows the software design paradigm of SimpleNLG (Gatt and Reiter, 2009). We explain the core grammar (morphology and syntax) and the lexicon of SimpleNL…

Morphological InflectionText Generation

SimpleNLG-IT: adapting SimpleNLG to Italian

2016-09-01 · WS 2016 9 · Aless Mazzei, ro, Cristina Battaglino, Cristina Bosco
Text Generation