# BEGIN Yura Desk bundle: library_codex.data_structure.SegmentTree
"""Point updates and range products for an arbitrary monoid.

Use this when values change one position at a time and a half-open interval
must be folded with an associative operation.  ``max_right`` and ``min_left``
also find the first boundary where a monotone predicate stops holding.
"""


class SegmentTree:
    __slots__ = ("n", "size", "log", "data", "op", "identity")

    def __init__(self, values, op, identity):
        if isinstance(values, int):
            n = values
            values = [identity] * n
        else:
            values = list(values)
            n = len(values)
        size = 1 << (n - 1).bit_length() if n else 1
        data = [identity] * (size << 1)
        data[size : size + n] = values
        for node in range(size - 1, 0, -1):
            data[node] = op(data[node << 1], data[node << 1 | 1])
        self.n = n
        self.size = size
        self.log = size.bit_length() - 1
        self.data = data
        self.op = op
        self.identity = identity

    def set(self, index, value):
        node = index + self.size
        data = self.data
        data[node] = value
        op = self.op
        node >>= 1
        while node:
            data[node] = op(data[node << 1], data[node << 1 | 1])
            node >>= 1

    def add(self, index, value):
        """indexの現在値をop(value, current)で置き換える。O(log N)。"""
        node = index + self.size
        data = self.data
        op = self.op
        data[node] = op(value, data[node])
        node >>= 1
        while node:
            data[node] = op(data[node << 1], data[node << 1 | 1])
            node >>= 1

    def get(self, index):
        return self.data[index + self.size]

    def tolist(self):
        """現在の要素列をlistで返す。O(N)。"""
        return self.data[self.size:self.size + self.n]

    def __str__(self):
        return str(self.tolist())

    def __repr__(self):
        return "SegmentTree(%r)" % self.tolist()

    def prod(self, left, right):
        left += self.size
        right += self.size
        first = self.identity
        second = self.identity
        data = self.data
        op = self.op
        while left < right:
            if left & 1:
                first = op(first, data[left])
                left += 1
            if right & 1:
                right -= 1
                second = op(data[right], second)
            left >>= 1
            right >>= 1
        return op(first, second)

    query = prod

    def all_prod(self):
        return self.data[1]

    def max_right(self, left, predicate):
        if left == self.n:
            return self.n
        left += self.size
        value = self.identity
        data = self.data
        op = self.op
        while True:
            while not left & 1:
                left >>= 1
            merged = op(value, data[left])
            if not predicate(merged):
                while left < self.size:
                    left <<= 1
                    merged = op(value, data[left])
                    if predicate(merged):
                        value = merged
                        left += 1
                return min(left - self.size, self.n)
            value = merged
            left += 1
            if left & -left == left:
                break
        return self.n

    def min_left(self, right, predicate):
        if right == 0:
            return 0
        right += self.size
        value = self.identity
        data = self.data
        op = self.op
        while True:
            right -= 1
            while right > 1 and right & 1:
                right >>= 1
            merged = op(data[right], value)
            if not predicate(merged):
                while right < self.size:
                    right = right << 1 | 1
                    merged = op(data[right], value)
                    if predicate(merged):
                        value = merged
                        right -= 1
                return max(0, right + 1 - self.size)
            value = merged
            if right & -right == right:
                break
        return 0

    def __getitem__(self, index):
        return self.get(index)
# END Yura Desk bundle: library_codex.data_structure.SegmentTree

# input
import sys
input = sys.stdin.readline
II = lambda : int(input())
MI = lambda : map(int, input().split())
LI = lambda : [int(a) for a in input().split()]
SI = lambda : input().rstrip()
LLI = lambda n : [[int(a) for a in input().split()] for _ in range(n)]
LSI = lambda n : [input().rstrip() for _ in range(n)]
MI_1 = lambda : map(lambda x:int(x)-1, input().split())
LI_1 = lambda : [int(a)-1 for a in input().split()]

mod = 998244353
inf = 1001001001001001001
ordalp = lambda s : ord(s)-65 if s.isupper() else ord(s)-97
ordallalp = lambda s : ord(s)-39 if s.isupper() else ord(s)-97
yes = lambda : print("Yes")
no = lambda : print("No")
yn = lambda flag : print("Yes" if flag else "No")

prinf = lambda ans : print(ans if ans < 1000001001001001001 else -1)
alplow = "abcdefghijklmnopqrstuvwxyz"
alpup = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
alpall = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
URDL = {'U':(-1,0), 'R':(0,1), 'D':(1,0), 'L':(0,-1)}
DIR_4 = [[-1,0],[0,1],[1,0],[0,-1]]
DIR_8 = [[-1,0],[-1,1],[0,1],[1,1],[1,0],[1,-1],[0,-1],[-1,-1]]
DIR_BISHOP = [[-1,1],[1,1],[1,-1],[-1,-1]]
prime60 = [2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59]
sys.set_int_max_str_digits(0)
# sys.setrecursionlimit(10**6)
# import pypyjit
# pypyjit.set_param('max_unroll_recursion=-1')

from collections import defaultdict,deque
from heapq import heappop,heappush
from bisect import bisect_left,bisect_right
DD = defaultdict
BSL = bisect_left
BSR = bisect_right


"""
monotone : argmin f(k, *) <= argmin f(k+1, *)
各行の最小値が単調に右にずれる

convex : 下に凸
concave : 上に凸
"""

def monotone_minima(h, w, select):
    """
    monotone の 最小値indexの配列
    bool select : a_(i,j) < a_(i,k) (j < k)
    """
    min_col = [0] * h
    que = [(0, h, 0, w)]
    while que:
        x1, x2, y1, y2 = que.pop()
        if x1 == x2: continue
        x = x1 + x2 >> 1
        best_y = y1
        for y in range(y1 + 1, y2):
            if select(x, best_y, y): best_y = y
        min_col[x] = best_y
        que.append((x+1, x2, best_y, y2))
        que.append((x1, x, y1, best_y+1))
    return min_col

def minplus_convolusion_convex_convex(a, b):
    n = len(a)
    m = len(b)
    c = [0] * (n + m - 1)
    i = j = 0
    c[0] = a[0] + b[0]
    for k in range(1, n+m-1):
        if j == m-1:
            i += 1
        elif i == n-1:
            j += 1
        elif a[i+1] + b[j] < a[i] + b[j+1]:
            i += 1
        else:
            j += 1
        c[k] = a[i] + b[j]
    return c

def minplus_convolusion_arbitrary_convex(a, b):
    n = len(a)
    m = len(b)
    def select(i, j, k):
        if i < k: return False
        if i - j >= m: return True
        return a[j] + b[i-j] >= a[k] + b[i-k]
    idx = monotone_minima(n + m - 1, n, select)
    c = [0] * (n + m - 1)
    for i , j in enumerate(idx):
        c[i] = a[j] + b[i-j]
    return c

def op(x, y):
    return minplus_convolusion_convex_convex(x, y)[:11]

n, q = MI()
s = LI()
s = [[0, x] for x in s]

seg = SegmentTree(s, op, [0])

for i in range(q):
    l, r, k = MI()
    print(seg.prod(l-1, r)[k])