class LcaDoubling: """ links[v] = { (u, w), (u, w), ... } (u:隣接頂点, w:辺の重み) というグラフ情報から、ダブリングによるLCAを構築。 任意の2頂点のLCAおよび距離を取得できるようにする """ def __init__(self, n, links, root=0): self.depths = [-1] * n self.distances = [-1] * n prev_ancestors = self._init_dfs(n, links, root) self.ancestors = [prev_ancestors] max_depth = max(self.depths) d = 1 while d < max_depth: next_ancestors = [prev_ancestors[p] for p in prev_ancestors] self.ancestors.append(next_ancestors) d <<= 1 prev_ancestors = next_ancestors def _init_dfs(self, n, links, root): q = [(root, -1, 0, 0)] direct_ancestors = [-1] * (n + 1) # 頂点数より1個長くし、存在しないことを-1で表す。末尾(-1)要素は常に-1 while q: v, p, dep, dist = q.pop() direct_ancestors[v] = p self.depths[v] = dep self.distances[v] = dist q.extend((u, v, dep + 1, dist + w) for u, w in links[v] if u != p) return direct_ancestors def get_lca(self, u, v): du, dv = self.depths[u], self.depths[v] if du > dv: u, v = v, u du, dv = dv, du tu = u tv = self.upstream(v, dv - du) if u == tv: return u for k in range(du.bit_length() - 1, -1, -1): mu = self.ancestors[k][tu] mv = self.ancestors[k][tv] if mu != mv: tu = mu tv = mv lca = self.ancestors[0][tu] assert lca == self.ancestors[0][tv] return lca def get_distance(self, u, v): lca = self.get_lca(u, v) return self.distances[u] + self.distances[v] - 2 * self.distances[lca] def upstream(self, v, k): i = 0 while k: if k & 1: v = self.ancestors[i][v] k >>= 1 i += 1 return v n = int(input()) links = [[] for i in range(n)] for i in range(n-1): u,v,w = map(int,input().split()) links[u].append([v,w]) links[v].append([u,w]) q = int(input()) xyz = [[int(i) for i in input().split()] for j in range(q)] lca = LcaDoubling(n,links) for i in range(q): x,y,z = xyz[i] xy = lca.get_lca(x,y) zxy = lca.get_lca(z,xy) ans = lca.get_distance(zxy,z) ans += lca.get_distance(zxy,y) ans += lca.get_distance(zxy,x) if xy != zxy: ans -= lca.get_distance(xy,zxy) yz = lca.get_lca(y,z) if yz != zxy: ans -= lca.get_distance(yz,zxy) zx = lca.get_lca(z,x) if zx != zxy: ans -= lca.get_distance(zx,zxy) print(ans)