from heapq import heappush, heappop
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
    edges[to, fr] = cost

def minDist(s):
    que = [(0, s)]
    dist = [float('inf')] * N
    dist[s] = 0
    while que:
        d, now = heappop(que)
        for (_, to), cost in edges.getrow(now).todok().items():
            nd = d + cost
            if dist[to] > nd:
                dist[to] = nd
                heappush(que, (nd, to))
    return dist

minDistS = minDist(0)
minDistP = minDist(P)
minDistQ = minDist(Q)

ans = -1

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