code: def dataset():
      n = 10
      features = datasets.Features(
          {
              "tokens": datasets.Sequence(datasets.Value("string")),
              "labels": datasets.Sequence(
                  datasets.ClassLabel(names=["negative", "positive"])
              ),
              "answers": datasets.Sequence(
                  {
                      "text": datasets.Value("string"),
                      "answer_start": datasets.Value("int32"),
                  }
              ),
              "id": datasets.Value("int64"),
          }
      )
      dataset = datasets.Dataset.from_dict(
          {
              "tokens": [["foo"] * 5] * n,
              "labels": [[1] * 5] * n,
              "answers": [{"answer_start": [97], "text": ["1976"]}]
              * 10,
              "id": list(range(n)),
          },
          features=features,
      )
      return dataset
  
imports: import contextlib
  import csv
  import json
  import os
  import sqlite3
  import tarfile
  import textwrap
  import zipfile
  import pyarrow
  import pyarrow.parquet
  import pytest
  import datasets
  import datasets.config
label_desc: Use image node_id 1 for calling a global function with example usage: dataset() and returns: dataset