import numpy as np
from scipy.sparse.csgraph import shortest_path
from scipy.sparse import lil_matrix

N, M, P, Q, T = map(int, input().split())
P -= 1
Q -= 1

edges = lil_matrix((N, N), dtype=int)

for _ in range(M):
    fr, to, cost = map(int, input().split())
    fr -= 1
    to -= 1
    edges[fr, to] = cost

minDistS = list(map(int, shortest_path(edges.tocsr(), directed=False, indices=0)))
minDistP = list(map(int, shortest_path(edges.tocsr(), directed=False, indices=P)))
minDistQ = list(map(int, shortest_path(edges.tocsr(), directed=False, indices=Q)))

ans = -1

if minDistS[P] + minDistP[Q] + minDistQ[0] <= T or minDistS[Q] + minDistQ[P] + minDistP[0] <= T:
    ans = T

for mid in range(N):
    time = minDistS[mid] * 2 + max(minDistP[mid], minDistQ[mid]) * 2
    if time <= T:
        ans = max(ans, (T - time) + minDistS[mid] * 2)

print(ans)