def distance(x1, y1, x2, y2):
  """Calculates the Euclidean distance between two points."""
  return ((x2 - x1)**2 + (y2 - y1)**2)**0.5
 
def calculate_stability(points):
  """Calculates the stability of a triumvirate."""
  distances = []
  for i in range(3):
    for j in range(i + 1, 3):
      distances.append(distance(points[i][0], points[i][1], points[j][0], points[j][1]))
  return max(distances) - min(distances)
 
def find_best_triumvirates(points):
  """Finds the best grouping of points into triumvirates."""
  n = len(points)
  triumvirates = []
  for i in range(0, n, 3):
    triumvirates.append([i, i + 1, i + 2])
  best_triumvirates = triumvirates
  best_score = sum(calculate_stability([points[j] for j in t]) for t in triumvirates)
 
  # Implement a more efficient search algorithm here to find the optimal grouping
  # (e.g., brute force, greedy, or a more advanced optimization technique)
 
  return best_triumvirates
 
def main():
  n = int(input())
  points = []
  for _ in range(n):
    x, y = map(int, input().split())
    points.append((x, y))
  best_triumvirates = find_best_triumvirates(points)
  for t in best_triumvirates:
    print(*t)
 
if __name__ == "__main__":
  main()

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