code: def specialized_ner_reader(file_path: str):
      original_examples = read_ner_from_tsv(file_path)
  
      def corpus(nlp: Language):
          for original_example in original_examples:
              doc = nlp.make_doc(original_example[0])
              with warnings.catch_warnings():
                  warnings.simplefilter("ignore", category=UserWarning)
                  spacy_example = Example.from_dict(
                      doc, original_example[1]
                  )
              yield spacy_example
  
      return corpus
  
file_path: scispacy/scispacy/base_project_code.py
imports: from typing import Optional, Callable, Iterable, Iterator
  from pathlib import Path
  import random
  import itertools
  import spacy
  import warnings
  from spacy.training import Corpus, Example
  from spacy.language import Language
  from scispacy.custom_tokenizer import combined_rule_tokenizer
  from scispacy.data_util import read_full_med_mentions, read_ner_from_tsv
label_desc: Use image node_id 5 for calling a global function with example usage: specialized_ner_reader(file_path) and returns: corpus