description: There is a city that can be represented as a square grid with corner points in (0, 0) and (10^6, 10^6).
  
  The city has n vertical and m horizontal streets that goes across the whole city, i. e. the i-th vertical streets goes from (x_i, 0) to (x_i, 10^6) and the j-th horizontal street goes from (0, y_j) to (10^6, y_j). 
  
  All streets are bidirectional. Borders of the city are streets as well.
  
  There are k persons staying on the streets: the p-th person at point (x_p, y_p) (so either x_p equal to some x_i or y_p equal to some y_j, or both).
  
  Let's say that a pair of persons form an inconvenient pair if the shortest path from one person to another going only by streets is strictly greater than the Manhattan distance between them.
  
  Calculate the number of inconvenient pairs of persons (pairs (x, y) and (y, x) are the same pair).
  
  Let's recall that Manhattan distance between points (x_1, y_1) and (x_2, y_2) is |x_1 - x_2| + |y_1 - y_2|.
  
  Input
  
  The first line contains a single integer t (1 ≤ t ≤ 1000) — the number of test cases.
  
  The first line of each test case contains three integers n, m and k (2 ≤ n, m ≤ 2 ⋅ 10^5; 2 ≤ k ≤ 3 ⋅ 10^5) — the number of vertical and horizontal streets and the number of persons.
  
  The second line of each test case contains n integers x_1, x_2, ..., x_n (0 = x_1 < x_2 < ... < x_{n - 1} < x_n = 10^6) — the x-coordinates of vertical streets.
  
  The third line contains m integers y_1, y_2, ..., y_m (0 = y_1 < y_2 < ... < y_{m - 1} < y_m = 10^6) — the y-coordinates of horizontal streets.
  
  Next k lines contains description of people. The p-th line contains two integers x_p and y_p (0 ≤ x_p, y_p ≤ 10^6; x_p ∈ \\{x_1, ..., x_n\} or y_p ∈ \\{y_1, ..., y_m\}) — the coordinates of the p-th person. All points are distinct.
  
  It guaranteed that sum of n doesn't exceed 2 ⋅ 10^5, sum of m doesn't exceed 2 ⋅ 10^5 and sum of k doesn't exceed 3 ⋅ 10^5.
  
  Output
  
  For each test case, print the number of inconvenient pairs.
  
  Example
  
  Input
  
  
  2
  2 2 4
  0 1000000
  0 1000000
  1 0
  1000000 1
  999999 1000000
  0 999999
  5 4 9
  0 1 2 6 1000000
  0 4 8 1000000
  4 4
  2 5
  2 2
  6 3
  1000000 1
  3 8
  5 8
  8 8
  6 8
  
  
  Output
  
  
  2
  5
  
  Note
  
  The second test case is pictured below: 
  
  <image>
  
  For example, points 3 and 4 form an inconvenient pair, since the shortest path between them (shown red and equal to 7) is greater than its Manhattan distance (equal to 5).
  
  Points 3 and 5 also form an inconvenient pair: the shortest path equal to 1000001 (shown green) is greater than the Manhattan distance equal to 999999.
  
  But points 5 and 9 don't form an inconvenient pair, since the shortest path (shown purple) is equal to its Manhattan distance.
solution: # ------------------- fast io --------------------
  import os
  import sys
  from io import BytesIO, IOBase
  
  BUFSIZE = 8192
  
  
  class FastIO(IOBase):
      newlines = 0
      
      def __init__(self, file):
          self._fd = file.fileno()
          self.buffer = BytesIO()
          self.writable = "x" in file.mode or "r" not in file.mode
          self.write = self.buffer.write if self.writable else None
      
      def read(self):
          while True:
              b = os.read(self._fd, max(os.fstat(self._fd).st_size, BUFSIZE))
              if not b:
                  break
              ptr = self.buffer.tell()
              self.buffer.seek(0, 2), self.buffer.write(b), self.buffer.seek(ptr)
          self.newlines = 0
          return self.buffer.read()
      
      def readline(self):
          while self.newlines == 0:
              b = os.read(self._fd, max(os.fstat(self._fd).st_size, BUFSIZE))
              self.newlines = b.count(b"\n") + (not b)
              ptr = self.buffer.tell()
              self.buffer.seek(0, 2), self.buffer.write(b), self.buffer.seek(ptr)
          self.newlines -= 1
          return self.buffer.readline()
      
      def flush(self):
          if self.writable:
              os.write(self._fd, self.buffer.getvalue())
              self.buffer.truncate(0), self.buffer.seek(0)
  
  
  class IOWrapper(IOBase):
      def __init__(self, file):
          self.buffer = FastIO(file)
          self.flush = self.buffer.flush
          self.writable = self.buffer.writable
          self.write = lambda s: self.buffer.write(s.encode("ascii"))
          self.read = lambda: self.buffer.read().decode("ascii")
          self.readline = lambda: self.buffer.readline().decode("ascii")
  
  
  sys.stdin, sys.stdout = IOWrapper(sys.stdin), IOWrapper(sys.stdout)
  input = lambda: sys.stdin.readline().rstrip("\r\n")
  
  # ------------------- fast io --------------------
  from math import ceil
  
  
  def prod(a, mod=10 ** 9 + 7):
      ans = 1
      for each in a:
          ans = (ans * each) % mod
      return ans
  
  
  def gcd(x, y):
      while y:
          x, y = y, x % y
      return x
  
  
  def lcm(a, b): return a * b // gcd(a, b)
  
  
  def binary(x, length=16):
      y = bin(x)[2:]
      return y if len(y) >= length else "0" * (length - len(y)) + y
  
  
  class SortedList:
      def __init__(self, iterable=[], _load=200):
          """Initialize sorted list instance."""
          values = sorted(iterable)
          self._len = _len = len(values)
          self._load = _load
          self._lists = _lists = [values[i:i + _load] for i in range(0, _len, _load)]
          self._list_lens = [len(_list) for _list in _lists]
          self._mins = [_list[0] for _list in _lists]
          self._fen_tree = []
          self._rebuild = True
      
      def _fen_build(self):
          """Build a fenwick tree instance."""
          self._fen_tree[:] = self._list_lens
          _fen_tree = self._fen_tree
          for i in range(len(_fen_tree)):
              if i | i + 1 < len(_fen_tree):
                  _fen_tree[i | i + 1] += _fen_tree[i]
          self._rebuild = False
      
      def _fen_update(self, index, value):
          """Update `fen_tree[index] += value`."""
          if not self._rebuild:
              _fen_tree = self._fen_tree
              while index < len(_fen_tree):
                  _fen_tree[index] += value
                  index |= index + 1
      
      def _fen_query(self, end):
          """Return `sum(_fen_tree[:end])`."""
          if self._rebuild:
              self._fen_build()
          
          _fen_tree = self._fen_tree
          x = 0
          while end:
              x += _fen_tree[end - 1]
              end &= end - 1
          return x
      
      def _fen_findkth(self, k):
          """Return a pair of (the largest `idx` such that `sum(_fen_tree[:idx]) <= k`, `k - sum(_fen_tree[:idx])`)."""
          _list_lens = self._list_lens
          if k < _list_lens[0]:
              return 0, k
          if k >= self._len - _list_lens[-1]:
              return len(_list_lens) - 1, k + _list_lens[-1] - self._len
          if self._rebuild:
              self._fen_build()
          
          _fen_tree = self._fen_tree
          idx = -1
          for d in reversed(range(len(_fen_tree).bit_length())):
              right_idx = idx + (1 << d)
              if right_idx < len(_fen_tree) and k >= _fen_tree[right_idx]:
                  idx = right_idx
                  k -= _fen_tree[idx]
          return idx + 1, k
      
      def _delete(self, pos, idx):
          """Delete value at the given `(pos, idx)`."""
          _lists = self._lists
          _mins = self._mins
          _list_lens = self._list_lens
          
          self._len -= 1
          self._fen_update(pos, -1)
          del _lists[pos][idx]
          _list_lens[pos] -= 1
          
          if _list_lens[pos]:
              _mins[pos] = _lists[pos][0]
          else:
              del _lists[pos]
              del _list_lens[pos]
              del _mins[pos]
              self._rebuild = True
      
      def _loc_left(self, value):
          """Return an index pair that corresponds to the first position of `value` in the sorted list."""
          if not self._len:
              return 0, 0
          
          _lists = self._lists
          _mins = self._mins
          
          lo, pos = -1, len(_lists) - 1
          while lo + 1 < pos:
              mi = (lo + pos) >> 1
              if value <= _mins[mi]:
                  pos = mi
              else:
                  lo = mi
          
          if pos and value <= _lists[pos - 1][-1]:
              pos -= 1
          
          _list = _lists[pos]
          lo, idx = -1, len(_list)
          while lo + 1 < idx:
              mi = (lo + idx) >> 1
              if value <= _list[mi]:
                  idx = mi
              else:
                  lo = mi
          
          return pos, idx
      
      def _loc_right(self, value):
          """Return an index pair that corresponds to the last position of `value` in the sorted list."""
          if not self._len:
              return 0, 0
          
          _lists = self._lists
          _mins = self._mins
          
          pos, hi = 0, len(_lists)
          while pos + 1 < hi:
              mi = (pos + hi) >> 1
              if value < _mins[mi]:
                  hi = mi
              else:
                  pos = mi
          
          _list = _lists[pos]
          lo, idx = -1, len(_list)
          while lo + 1 < idx:
              mi = (lo + idx) >> 1
              if value < _list[mi]:
                  idx = mi
              else:
                  lo = mi
          
          return pos, idx
      
      def add(self, value):
          """Add `value` to sorted list."""
          _load = self._load
          _lists = self._lists
          _mins = self._mins
          _list_lens = self._list_lens
          
          self._len += 1
          if _lists:
              pos, idx = self._loc_right(value)
              self._fen_update(pos, 1)
              _list = _lists[pos]
              _list.insert(idx, value)
              _list_lens[pos] += 1
              _mins[pos] = _list[0]
              if _load + _load < len(_list):
                  _lists.insert(pos + 1, _list[_load:])
                  _list_lens.insert(pos + 1, len(_list) - _load)
                  _mins.insert(pos + 1, _list[_load])
                  _list_lens[pos] = _load
                  del _list[_load:]
                  self._rebuild = True
          else:
              _lists.append([value])
              _mins.append(value)
              _list_lens.append(1)
              self._rebuild = True
      
      def discard(self, value):
          """Remove `value` from sorted list if it is a member."""
          _lists = self._lists
          if _lists:
              pos, idx = self._loc_right(value)
              if idx and _lists[pos][idx - 1] == value:
                  self._delete(pos, idx - 1)
      
      def remove(self, value):
          """Remove `value` from sorted list; `value` must be a member."""
          _len = self._len
          self.discard(value)
          if _len == self._len:
              raise ValueError('{0!r} not in list'.format(value))
      
      def pop(self, index=-1):
          """Remove and return value at `index` in sorted list."""
          pos, idx = self._fen_findkth(self._len + index if index < 0 else index)
          value = self._lists[pos][idx]
          self._delete(pos, idx)
          return value
      
      def bisect_left(self, value):
          """Return the first index to insert `value` in the sorted list."""
          pos, idx = self._loc_left(value)
          return self._fen_query(pos) + idx
      
      def bisect_right(self, value):
          """Return the last index to insert `value` in the sorted list."""
          pos, idx = self._loc_right(value)
          return self._fen_query(pos) + idx
      
      def count(self, value):
          """Return number of occurrences of `value` in the sorted list."""
          return self.bisect_right(value) - self.bisect_left(value)
      
      def __len__(self):
          """Return the size of the sorted list."""
          return self._len
      
      def __getitem__(self, index):
          """Lookup value at `index` in sorted list."""
          pos, idx = self._fen_findkth(self._len + index if index < 0 else index)
          return self._lists[pos][idx]
      
      def __delitem__(self, index):
          """Remove value at `index` from sorted list."""
          pos, idx = self._fen_findkth(self._len + index if index < 0 else index)
          self._delete(pos, idx)
      
      def __contains__(self, value):
          """Return true if `value` is an element of the sorted list."""
          _lists = self._lists
          if _lists:
              pos, idx = self._loc_left(value)
              return idx < len(_lists[pos]) and _lists[pos][idx] == value
          return False
      
      def __iter__(self):
          """Return an iterator over the sorted list."""
          return (value for _list in self._lists for value in _list)
      
      def __reversed__(self):
          """Return a reverse iterator over the sorted list."""
          return (value for _list in reversed(self._lists) for value in reversed(_list))
      
      def __repr__(self):
          """Return string representation of sorted list."""
          return 'SortedList({0})'.format(list(self))
  
  
  from bisect import bisect_left, bisect_right
  
  
  class Result:
      def __init__(self, index, value):
          self.index = index
          self.value = value
  
  
  class BinarySearch:
      def __init__(self):
          pass
      
      @staticmethod
      def greater_than(num: int, func, size: int = 1):
          """Searches for smallest element greater than num!"""
          if isinstance(func, list):
              index = bisect_right(func, num)
              if index == len(func):
                  return Result(None, None)
              else:
                  return Result(index, func[index])
          else:
              alpha, omega = 0, size - 1
              if func(omega) <= num:
                  return Result(None, None)
              while alpha < omega:
                  if func(alpha) > num:
                      return Result(alpha, func(alpha))
                  if omega == alpha + 1:
                      return Result(omega, func(omega))
                  mid = (alpha + omega) // 2
                  if func(mid) > num:
                      omega = mid
                  else:
                      alpha = mid
      
      @staticmethod
      def less_than(num: int, func, size: int = 1):
          """Searches for largest element less than num!"""
          if isinstance(func, list):
              index = bisect_left(func, num) - 1
              if index == -1:
                  return Result(None, None)
              else:
                  return Result(index, func[index])
          else:
              alpha, omega = 0, size - 1
              if func(alpha) >= num:
                  return Result(None, None)
              while alpha < omega:
                  if func(omega) < num:
                      return Result(omega, func(omega))
                  if omega == alpha + 1:
                      return Result(alpha, func(alpha))
                  mid = (alpha + omega) // 2
                  if func(mid) < num:
                      alpha = mid
                  else:
                      omega = mid
  bs = BinarySearch()
  for _ in range(int(input()) if True else 1):
      #n = int(input())
      n, m, k = map(int, input().split())
      # a, b = map(int, input().split())
      # c, d = map(int, input().split())
      xco = sorted(list(map(int, input().split())))
      yco = sorted(list(map(int, input().split())))
      xc, yc = set(xco), set(yco)
      
      
      persons = []
      ypo = []
      xpo = []
      ypod = {}
      xpod = {}
      for i in range(k):
          x, y = map(int, input().split())
          if x in xc and y in yc: continue
          persons += [(x, y)]
          if x in xc:
              ypo += [y]
              if x not in ypod:
                  ypod[x] = []
              ypod[x] += [y]
          else:
              if y not in xpod:
                  xpod[y] = []
              xpod[y] += [x]
              xpo += [x]
      ans = 0
      xpo = sorted(xpo)
      ypo = sorted(ypo)
      
      for x in xpod:
          xpod[x] = sorted(xpod[x])
      for y in ypod:
          ypod[y] = sorted(ypod[y])
      
      for x, y in persons:
          if x in xc:
              yh = bs.greater_than(y-1, yco).value
              yl = bs.less_than(y+1, yco).value
              # yl + 1 -> yh - 1
              c1 = bs.greater_than(yl, ypo).index
              c2 = bs.less_than(yh, ypo).index
              if c1 is None or c2 is None:continue
              ans += c2 - c1+1
              
              c1 = bs.greater_than(yl, ypod[x]).index
              c2 = bs.less_than(yh, ypod[x]).index
              if c1 is None or c2 is None:continue
              ans -= (c2 - c1 + 1)
              
          else:
              xh = bs.greater_than(x - 1, xco).value
              xl = bs.less_than(x + 1, xco).value
              c1 = bs.greater_than(xl, xpo).index
              c2 = bs.less_than(xh, xpo).index
              if c1 is None or c2 is None: continue
              ans += c2 - c1+1
              c1 = bs.greater_than(xl, xpod[y]).index
              c2 = bs.less_than(xh, xpod[y]).index
              if c1 is None or c2 is None: continue
              ans -= (c2 - c1 + 1)
              
              
      print(ans//2)