Template-free Data-to-Text Generation of Finnish Sports News
October 04, 2019 Β· Declared Dead Β· π Nordic Conference of Computational Linguistics
Repo contents: LICENSE, README.md
Authors
Jenna Kanerva, Samuel RΓΆnnqvist, Riina Kekki, Tapio Salakoski, Filip Ginter
arXiv ID
1910.01863
Category
cs.CL: Computation & Language
Citations
21
Venue
Nordic Conference of Computational Linguistics
Repository
https://github.com/scoopmatic/finnish-hockey-news-generation-paper
β 6
Last Checked
2 months ago
Abstract
News articles such as sports game reports are often thought to closely follow the underlying game statistics, but in practice they contain a notable amount of background knowledge, interpretation, insight into the game, and quotes that are not present in the official statistics. This poses a challenge for automated data-to-text news generation with real-world news corpora as training data. We report on the development of a corpus of Finnish ice hockey news, edited to be suitable for training of end-to-end news generation methods, as well as demonstrate generation of text, which was judged by journalists to be relatively close to a viable product. The new dataset and system source code are available for research purposes at https://github.com/scoopmatic/finnish-hockey-news-generation-paper.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Computation & Language
π
π
Old Age
π
π
Old Age
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
R.I.P.
π»
Ghosted
Language Models are Few-Shot Learners
R.I.P.
π»
Ghosted
RoBERTa: A Robustly Optimized BERT Pretraining Approach
R.I.P.
π»
Ghosted
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
R.I.P.
π»
Ghosted
Deep contextualized word representations
Died the same way β π Death by README
R.I.P.
π
Death by README
Momentum Contrast for Unsupervised Visual Representation Learning
R.I.P.
π
Death by README
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
R.I.P.
π
Death by README
Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach
R.I.P.
π
Death by README