code: def load_wn18(check_md5hash=False, add_reciprocal_rels=False):
      """Load the WN18 dataset.
  
      WN18 is a subset of Wordnet. It was first presented by :cite:`bordes2013translating`.
  
      .. warning::
          The dataset includes a large number of inverse relations that spilled to the test set, and its use in
          experiments has been deprecated. **Use WN18RR instead**.
  
      The WN18 dataset is loaded from file if it exists at the ``AMPLIGRAPH_DATA_HOME`` location.
      If ``AMPLIGRAPH_DATA_HOME`` is not set, the default  ``~/ampligraph_datasets`` is checked.
      If the dataset is not found at either location, it is downloaded and placed in ``AMPLIGRAPH_DATA_HOME``
      or ``~/ampligraph_datasets``.
  
      The dataset is divided in three splits:
  
      - `train`: 141,442 triples
      - `valid` 5,000 triples
      - `test` 5,000 triples
  
      ========= ========= ======= ======= ============ ===========
       Dataset  Train     Valid   Test    Entities     Relations
      ========= ========= ======= ======= ============ ===========
      WN18      141,442   5,000   5,000   40,943        18
      ========= ========= ======= ======= ============ ===========
  
      Parameters
      ----------
      check_md5hash: bool
          If `True` check the md5hash of the files (default: `False`).
  
      add_reciprocal_rels: bool
          Flag which specifies whether to add reciprocal relations. For every <s, p, o> in the dataset
          this creates a corresponding triple with reciprocal relation <o, p_reciprocal, s> (default: `False`).
  
      Returns
      -------
  
      splits: dict
          The dataset splits `{'train': train, 'valid': valid, 'test': test}`. Each split is a ndarray of shape (n, 3).
  
      Example
      -------
      >>> from ampligraph.datasets import load_wn18
      >>> X = load_wn18()
      >>> X['test'][:3]
      array([['06845599', '_member_of_domain_usage', '03754979'],
             ['00789448', '_verb_group', '01062739'],
             ['10217831', '_hyponym', '10682169']], dtype=object)
  
      """
  
      wn18 = DatasetMetadata(
          dataset_name="wn18",
          filename="wn18.zip",
          url="https://s3-eu-west-1.amazonaws.com/ampligraph/datasets/wn18.zip",
          train_name="train.txt",
          valid_name="valid.txt",
          test_name="test.txt",
          train_checksum="7d68324d293837ac165c3441a6c8b0eb",
          valid_checksum="f4f66fec0ca83b5ebe7ad7003404e61d",
          test_checksum="b035247a8916c7ec3443fa949e1ff02c",
      )
  
      return _load_dataset(
          wn18,
          data_home=None,
          check_md5hash=check_md5hash,
          add_reciprocal_rels=add_reciprocal_rels,
      )
  
imports: import hashlib
  import json
  import logging
  import os
  import urllib
  import zipfile
  from collections import namedtuple
  from pathlib import Path
  import numpy
  import pandas
label_desc: Use image node_id 11 for calling a global function with example usage: load_wn18(check_md5hash, add_reciprocal_rels) and returns: _load_dataset