code: def load_fb15k(check_md5hash=False, add_reciprocal_rels=False):
      """Load the FB15k dataset.
  
      FB15k is a split of Freebase, first proposed 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 FB15k-237 instead**.
  
      The FB15k 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`: 483,142 triples
      - `valid`: 50,000 triples
      - `test`: 59,071 triples
  
      ========= ========= ======= ======= ============ ===========
       Dataset  Train     Valid   Test    Entities     Relations
      ========= ========= ======= ======= ============ ===========
      FB15K     483,142   50,000  59,071  14,951        1,345
      ========= ========= ======= ======= ============ ===========
  
      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_fb15k
      >>> X = load_fb15k()
      >>> X['test'][:3]
      array([['/m/01qscs',
              '/award/award_nominee/award_nominations./award/award_nomination/award',
              '/m/02x8n1n'],
             ['/m/040db', '/base/activism/activist/area_of_activism', '/m/0148d'],
             ['/m/08966',
              '/travel/travel_destination/climate./travel/travel_destination_monthly_climate/month',
              '/m/05lf_']], dtype=object)
  
      """
  
      FB15K = DatasetMetadata(
          dataset_name="fb15k",
          filename="fb15k.zip",
          url="https://s3-eu-west-1.amazonaws.com/ampligraph/datasets/fb15k.zip",
          train_name="train.txt",
          valid_name="valid.txt",
          test_name="test.txt",
          train_checksum="5a87195e68d7797af00e137a7f6929f2",
          valid_checksum="275835062bb86a86477a3c402d20b814",
          test_checksum="71098693b0efcfb8ac6cd61cf3a3b505",
      )
  
      return _load_dataset(
          FB15K,
          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 13 for calling a global function with example usage: load_fb15k(check_md5hash, add_reciprocal_rels) and returns: _load_dataset