#yukicoder 650 行列木クエリ

#Heavy-Light decomposition  データ構造を使うならbuild必須なので注意
class HL_decomposition:
    class SegmentTree:  #前提mod1
        def __init__(self, n, identity_e, function): self._n = n; self._size = 1 << (n - 1).bit_length(); self._e = e = identity_e; self._f = function; self._node = [e] * 2 * self._size
        def build(self, A):
            for i,v in enumerate(A, start = self._size): self._node[i] = v
            for i in range(self._size - 1, 0, -1): self._node[i] = self._f(self._node[i<<1], self._node[i<<1|1])
        def update(self, index, value):
            i = self._size + index; self._node[i] = value
            while i - 1: i >>= 1; self._node[i] = self._f(self._node[i<<1], self._node[i<<1|1])
        def fold(self, Lt, Rt):
            Lt, Rt = Lt + self._size, Rt + self._size; vL = vR = self._e
            while Lt < Rt:
                if Lt & 1: vL = self._f(vL, self._node[Lt]); Lt += 1
                if Rt & 1: Rt -= 1; vR = self._f(self._node[Rt], vR)
                Lt >>= 1; Rt >>= 1
            return self._f(vL, vR)
    class SparseTable:  #前提mod2
        def __init__(self, n, identity_e, function): self._n = n; self._logn = (n - 1).bit_length(); self._size = 1 << self._logn; self._e = e = identity_e; self._f = function; self._T = [[e] * self._logn for _ in range(self._size)]; self._A = [e] * self._size
        def build(self, A):
            e, f, T = self._e, self._f, self._T; self._A = A = A + [e] * (self._size - self._n)
            for x in range(self._logn):
                t = 1 << x
                for s in range(t, self._size, t << 1):
                    T[s][x] = A[s]
                    for j in range(s + 1, s + t, +1): T[j][x] = f(T[j-1][x], A[j])
                for s in range(self._size - t - 1, -1, - t << 1):
                    T[s][x] = A[s]
                    for j in range(s - 1, s - t, -1): T[j][x] = f(A[j], T[j+1][x])
        def fold(self, Lt, Rt): Lt, Rt = max(0, Lt), min(self._size, Rt) - 1; x = (Lt ^ Rt).bit_length() - 1; return self._e if not 0 <= Lt <= Rt < self._size else self._A[Lt] if Lt == Rt else self._f( self._T[Lt][x], self._T[Rt][x] )

    def __init__(self, N, G, identity_e = 0, func = 'add'):
        #pos[v] = i, order[i] = v  頂点vのDFS順序がi番目
        #leader[i]: Heavy edgeの代表値のDFS順序
        #depth[i]: 再帰の深さ  parent[i]: ひとつ根側のDFS順序
        #A[i]: u - vパスの重みw。DFS順序が遅い頂点v側に入れる。pos[u] < pos[v] = i
        self._N = N; self._logN = logN = N.bit_length(); self._e = e = identity_e
        self._f = f = (lambda x,y: x + y) if func == 'add' else func
        self._G = G = [[(v, e) for v in S] for S in G] if N > 1 and isinstance(G[0][0],int) else G
        self._A = A = [e for _ in range(N)]; self.pos = pos = [-1] * N
        self.order = order = [-1] * N; self.leader = leader = [-1] * N; size = [1] * N
        self.depth = depth = [-1] * N; self.parent = parent = [-1] * N; Q = [(0, -1)]
        for now,back in Q:  #前処理
            for nxt,_ in G[now]:
                if nxt != back: Q.append((nxt, now))
        while Q: now,back = Q.pop(); size[back] += size[now] if back != -1 else 0
        Q.append((0, -1, e, 0, -1))  #HL分解
        for i in range(N):
            now, back, c, d, t = Q.pop(); pos[now], parent[i]= i, pos[back]
            order[i], A[i], depth[i] = now, c, d; leader[i] = t = t if t != -1 else i
            if size[now] > 1:  #部分木のうち最大サイズのものを最後にappend
                s, v, x = 0, now, e
                for nxt,w in G[now]:
                    if nxt == back: continue
                    if s < size[nxt]:
                        if s > 0: Q.append((v, now, x, d + 1, -1))
                        s, v, x = size[nxt], nxt, w
                    else: Q.append((nxt, now, w, d + 1, -1))
                Q.append((v, now, x, d, t))

    def build(self, use_SegTree = True, A = 'no need to import'):
        N, e, f = self._N, self._e, self._f
        if A != 'no need to import': self._A = A
        self._ST = ST = self.SegmentTree if use_SegTree else self.SparseTable
        self._obvST = obvST = ST(N, e, f); obvST.build(self._A)
        self._revST = revST = ST(N, e, f); revST.build(self._A[::-1])

    def LCA(self, u, v):  #O(logN)
        i, j = self.pos[u], self.pos[v]; c, d = self.depth[i], self.depth[j]
        if c > d: i, j, c, d = j, i, c, d
        s, t = self.leader[i], self.leader[j]
        for d in range(d - 1, c - 1, -1): j = self.parent[t]; t = self.leader[j]
        while s != t: i, j = self.parent[s], self.parent[t]; s, t = self.leader[i], self.leader[j]
        return self.order[ min(i,j) ]

    def update(self, index_u, value_v, weight = None):
        if weight == None: j, w = self.pos[index_u], value_v
        else: i, j, w = self.pos[index_u], self.pos[value_v], weight; i, j = (j, i) if i > j else (i, j); assert self.parent[j] == i, 'not connect Tree edge'
        self._A[j] = w; self._obvST.update(j, w); self._revST.update(self._N - 1 - j, w)

    def fold(self, u, v, path_query = False):  #u→vパスの作用値を取得
        Lt = Rt = self._e; f = self._f; i, j = self.pos[u], self.pos[v]
        c, d = self.depth[i], self.depth[j]; s, t = self.leader[i], self.leader[j]
        for c in range(c - 1, d - 1, -1): Lt = f( Lt, self._revST.fold(N - 1 - i, N - s) ); i = self.parent[s]; s = self.leader[i]
        for d in range(d - 1, c - 1, -1): Rt = f( self._obvST.fold(t, j + 1), Rt ); j = self.parent[t]; t = self.leader[j]
        while s != t: Lt, Rt = f( Lt, self._revST.fold(N-1-i,N-s) ), f( self._obvST.fold(t,j+1), Rt ); i, j = self.parent[s], self.parent[t]; s, t = self.leader[i], self.leader[j]
        if   i > j: LCA, Lt = j, f( Lt, self._revST.fold(N - i - 1, N - j - 1) )
        elif i < j: LCA, Rt = i, f( self._obvST.fold(i + 1, j + 1), Rt )
        else: LCA = i
        LCA = self._e if path_query else self._A[LCA]; return f( f(Lt, LCA), Rt )

#行列累乗  1行N列の行列は[[1, 2, ...]] と2重括弧に自動変換するので注意
class matrix_pow:
    def __init__(self,MOD=998244353): self._MOD=MOD
    def eye(self,N):  #単位行列の作成
        return [[1 if i==j else 0 for j in range(N)] for i in range(N)]
    def add(self,A,B):  #行列の加算
        if isinstance(A[0],int): A=[A]
        if isinstance(B[0],int): B=[B]
        assert len(A)   ==len(B),    'not same size'
        assert len(A[0])==len(B[0]), 'not same size'
        nG=[[0]*max(len(A[i]) for i in range(len(A))) for _ in range(len(A))]
        for h in range(len(nG)):
            for w in range(len(nG[h])):
                if len(A[h])<w: nG[h][w]+=A[h][w]
                if len(B[h])<w: nG[h][w]+=B[h][w]
                nG[h][w]%=self._MOD
        return nG
    def mul(self,A,B):  #行列積  L行M列 * M行N列 = L行N列
        if isinstance(A[0],int): A=[A]
        if isinstance(B[0],int): B=[B]
        assert len(A[0])==len(B),    'cannot calcurate'
        nG=[[0]*max(len(B[i]) for i in range(len(B))) for _ in range(len(A))]
        for h in range(len(nG)):
            for w in range(len(nG[0])):
                for x in range(len(A[0])):
                    nG[h][w]+=A[h][x]*B[x][w]%self._MOD; nG[h][w]%=self._MOD
        return nG


#入力受取
N = int(input())
G = [[] for _ in range(N)]
H = []
for _ in range(N - 1):
    a,b = map(int,input().split())
    G[a].append(b)
    G[b].append(a)
    H.append((a,b))

#HLDに乗せる  初期値は単位行列
mp = matrix_pow(10 ** 9 + 7)
HLD = HL_decomposition(N, G, [[1,0], [0,1]], mp.mul)
HLD.build(True)

#クエリを処理
for _ in range(int(input())):
    t = list(input().split())
    if t[0] == 'x':
        i,w,x,y,z = map(int, t[1:])
        u,v = H[i]
        HLD.update(u, v, [[w,x],[y,z]])
    if t[0] == 'g':
        i,j = map(int, t[1:])
        ((w,x),(y,z)) = HLD.fold(i, j, True)
        print(w,x,y,z)