code: def get_xtreme_pos_example(
      sentence, example_id, features
  ) -> Mapping[str, Union[str, Sequence[str]]]:
      """Processes an annotated sentence into an example for the xtreme_pos dataset.
  
      This function adds a further check ensuring that, at a given position in a
      sentence, both the token and the upos label are not empty.
      This is done for consistency with the xtreme implementation in other
      libraries, such as HuggingFace (rf. line 955):
      https://github.com/huggingface/datasets/blob/e6f1352fe19679de897f3d962e616936a17094f5/datasets/xtreme/xtreme.py
  
      Args:
        sentence: the annotated sentence parsed with the conllu library.
        example_id: the example_id of the example, which will be used if the `idx`
          feature is present but not defined in the annotated sentence.
        features: the features defined in the output example.
  
      Returns:
        An example to be serialized.
      """
      del example_id
      example = {feature: [] for feature in features}
      for token in sentence:
          if token["form"] != "_" and token["upos"] != "_":
              example["tokens"].append(token["form"])
              example["upos"].append(token["upos"])
      return example
  
file_path: datasets/tensorflow_datasets/core/dataset_builders/conll/conllu_dataset_builder.py
imports: from typing import Callable, List, Mapping, Optional, OrderedDict, Sequence, Union
  from etils import epath
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import dataset_info
  from tensorflow_datasets.core import lazy_imports_lib
  from tensorflow_datasets.core import split_builder
  from tensorflow_datasets.core.features import feature
  from tensorflow_datasets.core.features.features_dict import FeaturesDict
label_desc: Use image node_id 2 for calling a global function with example usage: get_xtreme_pos_example(sentence, example_id, features) and returns: example