code: def test_insert(self):
      a1 = sample1
      a61 = a1.insert_field_before_indices("x", [0], ["test"])
      a62 = a1.insert_field_before_indices(
          "x",
          [0, 2, 4],
          ["Wang", "Xiao", ["fdu", "jiangwan", "cross_2"]],
      )
      a63 = a1.insert_field_after_indices(
          "x", [len(a1.x) - 1], [[" haha", "test"]]
      )
      a64 = a1.insert_field_after_indices(
          "x",
          [0, 2, 7],
          ["Wang", "Xiao", ["fdu", "jiangwan", "cross_2"]],
      )
      self.assertEqual(
          a61.dump(),
          {
              "doc_key": "doc_key1",
              "sentences": [
                  ["test", "I", "love", "my", "pet", "Anna", "."],
                  ["She", "is", "my", "favorite", "."],
              ],
              "speakers": [
                  ["sp_ins", "sp1", "sp1", "sp1", "sp1", "sp1", "sp1"],
                  ["sp1", "sp1", "sp1", "sp1", "sp1"],
              ],
              "clusters": [[[3, 4], [5, 5], [7, 7]]],
              "constituents": [
                  [1, 1, "0-I-C"],
                  [2, 2, "1-love-C"],
                  [3, 3, "2-my-C"],
                  [4, 4, "3-pet-C"],
                  [5, 5, "4-Anna-C"],
                  [6, 6, "5-.-C"],
                  [7, 7, "6-She-C"],
                  [8, 8, "7-is-C"],
                  [9, 9, "8-my-C"],
                  [10, 10, "9-favorite-C"],
                  [11, 11, "10-.-C"],
              ],
              "ner": [
                  [1, 1, "0-I-N"],
                  [2, 2, "1-love-N"],
                  [3, 3, "2-my-N"],
                  [4, 4, "3-pet-N"],
                  [5, 5, "4-Anna-N"],
                  [6, 6, "5-.-N"],
                  [7, 7, "6-She-N"],
                  [8, 8, "7-is-N"],
                  [9, 9, "8-my-N"],
                  [10, 10, "9-favorite-N"],
                  [11, 11, "10-.-N"],
              ],
              "sample_id": None,
          },
      )
      self.assertEqual(
          a62.dump(),
          {
              "doc_key": "doc_key1",
              "sentences": [
                  [
                      "Wang",
                      "I",
                      "love",
                      "Xiao",
                      "my",
                      "pet",
                      "fdu",
                      "jiangwan",
                      "cross_2",
                      "Anna",
                      ".",
                  ],
                  ["She", "is", "my", "favorite", "."],
              ],
              "speakers": [
                  [
                      "sp_ins",
                      "sp1",
                      "sp1",
                      "sp_ins",
                      "sp1",
                      "sp1",
                      "sp_ins",
                      "sp_ins",
                      "sp_ins",
                      "sp1",
                      "sp1",
                  ],
                  ["sp1", "sp1", "sp1", "sp1", "sp1"],
              ],
              "clusters": [[[4, 5], [9, 9], [11, 11]]],
              "constituents": [
                  [1, 1, "0-I-C"],
                  [2, 2, "1-love-C"],
                  [4, 4, "2-my-C"],
                  [5, 5, "3-pet-C"],
                  [9, 9, "4-Anna-C"],
                  [10, 10, "5-.-C"],
                  [11, 11, "6-She-C"],
                  [12, 12, "7-is-C"],
                  [13, 13, "8-my-C"],
                  [14, 14, "9-favorite-C"],
                  [15, 15, "10-.-C"],
              ],
              "ner": [
                  [1, 1, "0-I-N"],
                  [2, 2, "1-love-N"],
                  [4, 4, "2-my-N"],
                  [5, 5, "3-pet-N"],
                  [9, 9, "4-Anna-N"],
                  [10, 10, "5-.-N"],
                  [11, 11, "6-She-N"],
                  [12, 12, "7-is-N"],
                  [13, 13, "8-my-N"],
                  [14, 14, "9-favorite-N"],
                  [15, 15, "10-.-N"],
              ],
              "sample_id": None,
          },
      )
      self.assertEqual(
          a63.dump(),
          {
              "doc_key": "doc_key1",
              "sentences": [
                  ["I", "love", "my", "pet", "Anna", "."],
                  ["She", "is", "my", "favorite", ".", " haha", "test"],
              ],
              "speakers": [
                  ["sp1", "sp1", "sp1", "sp1", "sp1", "sp1"],
                  [
                      "sp1",
                      "sp1",
                      "sp1",
                      "sp1",
                      "sp1",
                      "sp_ins",
                      "sp_ins",
                  ],
              ],
              "clusters": [[[2, 3], [4, 4], [6, 6]]],
              "constituents": [
                  [0, 0, "0-I-C"],
                  [1, 1, "1-love-C"],
                  [2, 2, "2-my-C"],
                  [3, 3, "3-pet-C"],
                  [4, 4, "4-Anna-C"],
                  [5, 5, "5-.-C"],
                  [6, 6, "6-She-C"],
                  [7, 7, "7-is-C"],
                  [8, 8, "8-my-C"],
                  [9, 9, "9-favorite-C"],
                  [10, 10, "10-.-C"],
              ],
              "ner": [
                  [0, 0, "0-I-N"],
                  [1, 1, "1-love-N"],
                  [2, 2, "2-my-N"],
                  [3, 3, "3-pet-N"],
                  [4, 4, "4-Anna-N"],
                  [5, 5, "5-.-N"],
                  [6, 6, "6-She-N"],
                  [7, 7, "7-is-N"],
                  [8, 8, "8-my-N"],
                  [9, 9, "9-favorite-N"],
                  [10, 10, "10-.-N"],
              ],
              "sample_id": None,
          },
      )
      self.assertEqual(
          a64.dump(),
          {
              "doc_key": "doc_key1",
              "sentences": [
                  [
                      "I",
                      "Wang",
                      "love",
                      "my",
                      "Xiao",
                      "pet",
                      "Anna",
                      ".",
                  ],
                  [
                      "She",
                      "is",
                      "fdu",
                      "jiangwan",
                      "cross_2",
                      "my",
                      "favorite",
                      ".",
                  ],
              ],
              "speakers": [
                  [
                      "sp1",
                      "sp_ins",
                      "sp1",
                      "sp1",
                      "sp_ins",
                      "sp1",
                      "sp1",
                      "sp1",
                  ],
                  [
                      "sp1",
                      "sp1",
                      "sp_ins",
                      "sp_ins",
                      "sp_ins",
                      "sp1",
                      "sp1",
                      "sp1",
                  ],
              ],
              "clusters": [[[3, 5], [6, 6], [8, 8]]],
              "constituents": [
                  [0, 0, "0-I-C"],
                  [2, 2, "1-love-C"],
                  [3, 3, "2-my-C"],
                  [5, 5, "3-pet-C"],
                  [6, 6, "4-Anna-C"],
                  [7, 7, "5-.-C"],
                  [8, 8, "6-She-C"],
                  [9, 9, "7-is-C"],
                  [13, 13, "8-my-C"],
                  [14, 14, "9-favorite-C"],
                  [15, 15, "10-.-C"],
              ],
              "ner": [
                  [0, 0, "0-I-N"],
                  [2, 2, "1-love-N"],
                  [3, 3, "2-my-N"],
                  [5, 5, "3-pet-N"],
                  [6, 6, "4-Anna-N"],
                  [7, 7, "5-.-N"],
                  [8, 8, "6-She-N"],
                  [9, 9, "7-is-N"],
                  [13, 13, "8-my-N"],
                  [14, 14, "9-favorite-N"],
                  [15, 15, "10-.-N"],
              ],
              "sample_id": None,
          },
      )
  
file_path: textflint/test/input/component/sample/test_coref_sample.py
imports: from textflint.input.component.sample.coref_sample import *
  import unittest
  import random
  from test.data.coref_debug import CorefDebug
label_desc: Use image node_id 8 for calling the TestCorefSample obj's underlying member method code with example usage: obj.test_insert() without return types