def mean_precision(j1, j2):
    """
    Calculate the Precision Index among judges for a given set of evaluations.
    In particular, the function takes in input two sets of evaluations (one for each judges)
    referring to a single score for a given systems.
    For *each* judge, the function computes $P(ji) = P(j1 \cap j2) / P(ji)$, namely the precision 
    of evaluations of considered judge $ji$.
    The two values, $P(j1)$ and P(j2), are then combined by an Harmonic Mean, that is 
    finally returned by the function.
    
    Parameters:
    -----------
    
    j1: set of evaluations of the first judge, corresponding to a **single** score for a **single**
        system (e.g., "Method-Comment Aggreement" in Project "X")
    j2: set of evaluations of the second judge (see above for further details)
    
    Returns:
    --------
    
    pj1: Precision associated to the first judge
    pj2: Precision associated to the second judge
    F: Armonic Mean between pj1 and pj2
    """
    
    pj1 = 0.0 if not len(j1) else len(j1.intersection(j2))/len(j1)
    pj2 = 0.0 if not len(j2) else len(j2.intersection(j1))/len(j2)
    if (pj1 == pj2 == 0.0):
        return 0.0, 0.0, 0.0
    f = 2 * ((pj1 * pj2) / (pj1 + pj2))
    return pj1, pj2, f