The dataset contains several key columns: input_text and target_text. The input_text column includes the infobox and first paragraph of a Wikipedia biography, providing essential information about the individual's background, accomplishments, and notable features. The target_text column consists of the complete biography text extracted from the corresponding Wikipedia page.
In order to facilitate model training and validation, the dataset is divided into three main files: train.csv, val.csv, and test.csv. The train.csv file contains pairs of input text and target text for model training. It serves as a fundamental resource to develop accurate language generation models by providing abundant examples for learning to generate coherent biographical texts.
The val.csv file provides further validation data consisting of additional Wikipedia biographies with their corresponding infoboxes and first paragraphs. This subset allows researchers to evaluate their trained models' performance on unseen examples during development or fine-tuning stages.
Finally, the test.csv file offers a separate set of input texts paired with corresponding target texts for generating complete biographies using pre-trained models or newly developed algorithms. The purpose of this file is to benchmark system performance on unseen data in order to assess generalization capabilities.
This extended description aims to provide an informative overview of the dataset structure, its intended use cases in natural language processing research tasks such as text generation or summarization. Researchers can leverage this comprehensive collection to advance various applications in automatic biography writing systems or content generation tasks that require coherent textual output based on provided partial information extracted from an infobox or initial paragraph sources from online encyclopedias like Wikipedia