Improving Data-to-Text Generation via Preserving High-Frequency Phrases and Fact-Checking
Transforming numerical data into natural language descriptions (data-to-text) requires presenting the data in the correct context, supplementing plausible details, and creating an overall coherent and non-conflicting narrative. In this work, we propose a generate-extract-correct pipeline for the tas...
保存先:
| 出版年: | URI:https://journals.openedition.org/ijcol, |
|---|---|
| 主要な著者: | , , |
| フォーマット: | Article ou chapitre numérique |
| 言語: | Anglais |
| 出版事項: |
IJCoL
2021
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| オンライン･アクセス: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |