Aims: The development of automatic tools to identify, characterize, and delineate abnormal ventricular potentials (AVPs) in post-ischemic ventricular tachycardia (VT) electrograms is still an open research issue. As a significant amount of annotated data is required for this purpose, the lack of open and annotated datasets hampers the research progress in this field. This work presents a new open dataset that will be made available on Physionet by October 2023, which was recorded, annotated, and validated in the framework of the "Ablation Reinforcement by computer-aided Guidance and Optimization: ARGO study" project. Materials and Methods: The proposed dataset includes about 2000 anonymized high-quality signals obtained from nine post-ischemic VT patients. The dataset is composed of 2.5s bipolar electrograms, the corresponding unipolar electrograms, and twelve surface ECG leads. Electrophysiological recordings were performed with the CARTO®3 system by Biosense-Webster at 1 kHz, with a resolution of 0.003 mV, during left ventricle electroanatomic mapping using PentaRay 2-6-2 mm, ThermoCool SmartTouch and ThermoCool SmartTouch SF catheters. Moreover, all the information for the reconstruction of the electroanatomic maps is also provided. For each bipolar electrogram, the corresponding label (i.e., physiological or AVP) is reported, and, in case of AVPs, onset and end of the AVP is reported. The annotation of the EGMs, in terms of label and delineation, and the validation of the entire dataset has been performed by a group of four expert electrophysiologists using an ad-hoc MATLAB graphical user interface that was implemented for this purpose. Significance: Given the current profound lack of available open and annotated datasets in this field, the ARGO dataset could represent a valuable tool to enable the effective development and benchmarking of AVP detection and delineation algorithms, their characterization, but also to encourage collaboration across the research community.