import heapq

class Graph:
    def __init__(self,V,edges=None,graph=None,directed=False,weighted=False,inf=float("inf")):
        self.V=V
        self.directed=directed
        self.weighted=weighted
        self.inf=inf
        if graph!=None:
            self.graph=graph
            """
            self.edges=[]
            for i in range(self.V):
                if self.weighted:
                    for j,d in self.graph[i]:
                        if self.directed or not self.directed and i<=j:
                            self.edges.append((i,j,d))
                else:
                    for j in self.graph[i]:
                        if self.directed or not self.directed and i<=j:
                            self.edges.append((i,j))
            """
        else:
            self.edges=edges
            self.graph=[[] for i in range(self.V)]
            if weighted:
                for i,j,d in self.edges:
                    self.graph[i].append((j,d))
                    if not self.directed:
                        self.graph[j].append((i,d))
            else:
                for i,j in self.edges:
                    self.graph[i].append(j)
                    if not self.directed:
                        self.graph[j].append(i)

    def Dijkstra(self,s,route_restoration=False):
        dist=[self.inf]*self.V
        dist[s]=0
        queue=[(0,s)]
        if route_restoration:
            parents=[None]*self.V
        while queue:
            dx,x=heapq.heappop(queue)
            if dist[x]<dx:
                continue
            for y,dy in self.graph[x]:
                if dist[y]>dx+dy:
                    dist[y]=dx+dy
                    if route_restoration:
                        parents[y]=x
                    heapq.heappush(queue,(dist[y],y))
        if route_restoration:
            return dist,parents
        else:
            return dist

    def Bellman_Ford(self,s,route_restoration=False):
        dist=[self.inf]*self.V
        dist[s]=0
        if route_restoration:
            parents=[None]*self.V
        for _ in range(self.V-1):
            for i,j,d in self.edges:
                if dist[j]>dist[i]+d:
                    dist[j]=dist[i]+d
                    if route_restoration:
                        parents[j]=i
                if not self.directed and dist[i]>dist[j]+d:
                    dist[i]=dist[j]+d
                    if route_restoration:
                        parents[i]=j
        negative_cycle=[]
        for i,j,d in self.edges:
            if dist[j]>dist[i]+d:
                negative_cycle.append(j)
            if not self.directed and dist[i]>dist[j]+d:
                negative_cycle.append(i)
        if negative_cycle:
            is_negative_cycle=[False]*self.V
            for i in negative_cycle:
                if is_negative_cycle[i]:
                    continue
                else:
                    queue=deque([i])
                    is_negative_cycle[i]=True
                    while queue:
                        x=queue.popleft()
                        for y,d in self.graph[x]:
                            if not is_negative_cycle[y]:
                                queue.append(y)
                                is_negative_cycle[y]=True
                                if route_restoration:
                                    parents[y]=x
            for i in range(self.V):
                if is_negative_cycle[i]:
                    dist[i]=-self.inf
        if route_restoration:
            return dist,parents
        else:
            return dist

N,M,Q=map(int,input().split())
edges=[]
for m in range(M):
    u,v,w=map(int,input().split())
    u-=1;v-=1
    w=-w
    edges.append((u,v,w))
inf=1<<60
G=Graph(N,edges=edges,directed=True,weighted=True,inf=inf)
dist=G.Bellman_Ford(0)
E=[]
for u,v,w in edges:
    w+=dist[u]-dist[v]
    E.append((u,v,w))
use=[1]*M
for j in map(int,input().split()):
    j-=1
    use[j]^=1
    edges=[]
    for m in range(M):
        if use[m]:
            edges.append(E[m])
    G=Graph(N,edges=edges,directed=True,weighted=True,inf=inf)
    ans=G.Dijkstra(0)[N-1]
    if ans==inf:
        ans="NaN"
    else:
        ans+=dist[N-1]-dist[0]
        ans=-ans
    print(ans)