Counting stars in the Cradle of Orion

As the field of star formation dives into the era of big data, we are now faced with the challenges behind reliable and unbiased applications of artificial intelligence and machine learning techniques. This is in large part due to the data available to validate machine-learning results, which are often susceptible to small numbers or limited to the specifications of a few larger-scale surveys. To tackle this, we revisited the published literature targeting the Orion star-formation complex under the framework of the NEMESIS (New Evolutionary Model for Early stages of Stars with Intelligent Systems) project to build a polyvalent training and validation sample Young Stellar Objects (YSOs). As a result, we have curated the region's most extensive panchromatic data collection, including data for more than 25,000 YSO candidates in the field of view of the Orion constellation, a more significant number of YSOs than ever mentioned in SIMBAD for the region. By reviewing the peer-reviewed literature beyond that included on CDS and collating previously observed data for these objects, we spectroscopically confirmed about 1/4 of this sample as definitely young. We present the main aspects of this catalogue, which include accretion and youth-related emission and absorption lines, spectral types, rotational properties, variability features, binarity information, and added value quantities such as SEDs and their derived quantities, uniformised YSO classes, and much more. Finally, we also illustrate the usability of the catalogue by showcasing some of the machine-learn applications developed by the NEMESIS team to explore star formation in the solar neighbourhood.