class_docstr: The NELL dataset, a knowledge graph from the
  `"Toward an Architecture for Never-Ending Language Learning"
  <https://www.cs.cmu.edu/~acarlson/papers/carlson-aaai10.pdf>`_ paper.
  The dataset is processed as in the
  `"Revisiting Semi-Supervised Learning with Graph Embeddings"
  <https://arxiv.org/abs/1603.08861>`_ paper.
  
  .. note::
  
      Entity nodes are described by sparse feature vectors of type
      :class:`torch.sparse_csr_tensor`.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      transform (callable, optional): A function/transform that takes in an
          :obj:`torch_geometric.data.Data` object and returns a transformed
          version. The data object will be transformed before every access.
          (default: :obj:`None`)
      pre_transform (callable, optional): A function/transform that takes in
          an :obj:`torch_geometric.data.Data` object and returns a
          transformed version. The data object will be transformed before
          being saved to disk. (default: :obj:`None`)
      force_reload (bool, optional): Whether to re-process the dataset.
          (default: :obj:`False`)
  
  **STATS:**
  
  .. list-table::
      :widths: 10 10 10 10
      :header-rows: 1
  
      * - #nodes
        - #edges
        - #features
        - #classes
      * - 65,755
        - 251,550
        - 61,278
        - 186
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code: def __init__(
      self,
      root: str,
      transform: Optional[Callable] = None,
      pre_transform: Optional[Callable] = None,
      force_reload: bool = False,
  ) -> None:
      super().__init__(
          root, transform, pre_transform, force_reload=force_reload
      )
      self.load(self.processed_paths[0])
  
file_path: pytorch_geometric/torch_geometric/datasets/nell.py
imports: import os
  import os.path
  from typing import Callable, List, Optional
  from torch_geometric.data import InMemoryDataset, download_url, extract_tar
  from torch_geometric.io import fs, read_planetoid_data
label_desc: Use image node_id 1 to create a new NELL object from inherited base classes: InMemoryDataset with example: obj = NELL(root, transform, pre_transform, force_reload)