Data-to-Text Generation ... A classic problem in natural-language generation (NLG) involves taking structured data, such as a table, as input, and producing text ...

Data-to-Text Generation (D2T NLG) can be described as Natural Language Generation from structured input.

The Data2Text (or Data-to-Text) project aims to automatically generate fluent and fact-based descriptions or utterances given data tables.

Data-to-text (D2T) generation describes the task of verbalizing data, often given as attribute-value pairs. While this task is relevant for many different data ...

11 авг. 2023 г. · Data-to-text Generation (D2T) aims to generate textual natural language statements that can fluently and precisely describe the structured ...

8 июн. 2022 г. · Data-to-text generation refers to the task of generating textual output from non-linguistic input such as database tables, spreadsheets, or ... Introduction · Model · Results · Discussion

28 июн. 2023 г. · In this paper, we propose a novel approach that goes beyond traditional one-shot generation methods by introducing a multi-step process ...

This survey offers a consolidated view into the neural D2T paradigm with a structured examination of the approaches, benchmark datasets, and evaluation ...

MTL-data-to-text is specially designed for data-to-text generation tasks, such as KG-to-text generation (AxtarishNLG, DART), table-to-text generation (WikiBio, ...

Abstract. Data-to-text generation involves transforming structured data, often represented as predicate-argument tuples, into coherent textual descriptions.