Transforming dense, detailed, unstructured text into an interpretable and summarised table, also colloquially known as Text-to-Table generation, is an essential task for information retrieval. Current methods, however, miss out on how and what complex information to extract; they also lack the ability to infer data from the text. In this paper, we introduce a versatile approach, Map&Make, which "dissects" text into propositional atomic statements. This facilitates granular decomposition to extract the latent schema. The schema is then used to populate the tables that capture the qualitative nuances and the quantitative facts in the original text. Our approach is tested against two challenging datasets, Rotowire, renowned for its complex and multi-table schema, and Livesum, which demands numerical aggregation. By carefully identifying and correcting hallucination errors in Rotowire, we aim to achieve a cleaner and more reliable benchmark. We evaluate our method rigorously on a comprehensive suite of comparative and referenceless metrics. Our findings demonstrate significant improvement results across both datasets with better interpretability in Text-to-Table generation. Moreover, through detailed ablation studies and analyses, we investigate the factors contributing to superior performance and validate the practicality of our framework in structured summarization tasks.

Many times, sports have been at the leading edge of data analytics. The book "Moneyball" was one of the first popular books to bring the basic concepts behind data analytics and data science to the general audience. Fantasy leagues, sabermetrics and even games like "Strat-O-Matic" baseball and basketball provided an introduction into basic statistical concepts. And it now seems that sports, in this case the National Basketball Association (NBA), are breaking new ground with another data analytics topic: who owns the data? The National Basketball Players Association recently banned NBA teams from using a player's wearable data in contract negotiations or other transactions (see "NBA Bans Teams From Using Wearable Data In Contract Negotiations").

Then, Friday night on MSG, there was Carmelo Anthony, who in an age of artificial intelligence, seems to have been abundantly blessed. With 43.7 seconds left, Knicks up, 107-102, Charlotte's Kemba Walker missed his second of two free throws. The ball bounced off the rim and to the right, where Anthony held the nearest-to-the-basket position. But what should've been an easy rebound became the Hornets' ball. Well, Anthony tried to re-invent basketball.