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Magnetic polarity inversion lines (PILs) in solar active regions are key to triggering flares and eruptions. Recently, engineered PIL features have been used for predicting solar eruptions. Derived from the original PIL dataset, using line-of-sight (LoS) magnetograms provided by the Solar Dynamics Observatory's (SDO) Helioseismic and Magnetic Imager (HMI) Active Region Patches (HARPs), we provide a publicly available comprehensive dataset in a supervised format, where each instance includes a raster of Polarity Inversion Lines (PILs), one of the polarity convex hull, and a multivariate time-series of properties related to PILs. Using SDO-GOES integrated flares historical data covering May 2010 to January 2019, we have assigned each of the instances their corresponding class of flare, FQ, C, M or X. By integrating these diverse data modalities, our approach aims to improve the accuracy of solar flare predictions. Initial findings suggest that the multimodal approach can uncover new patterns and relationships, potentially leading to breakthroughs in predictive accuracy and more effective mitigation strategies against the impacts of solar activities.