class_docstr: Base class for LIT annotator components.
  
  Annotators are for adding extra fields to datapoints, using a model to
  annotate datapoints given their feature values.
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docstr: Annotate the provided inputs.
  
  Args:
    inputs: sequence of inputs, modified in-place.
    dataset: dataset which the examples belong to.
    dataset_spec_to_annotate: spec to add new annotated fields to, modified
      in-place. If none provided, then no spec is updated.
  
  Returns:
    Updated spec for the dataset, given the new annotations.
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code: def annotate(
      self,
      inputs: list[dict[str, Any]],
      dataset: lit_dataset.Dataset,
      dataset_spec_to_annotate: Optional[types.Spec] = None,
  ):
      """Annotate the provided inputs.
  
      Args:
        inputs: sequence of inputs, modified in-place.
        dataset: dataset which the examples belong to.
        dataset_spec_to_annotate: spec to add new annotated fields to, modified
          in-place. If none provided, then no spec is updated.
  
      Returns:
        Updated spec for the dataset, given the new annotations.
      """
      pass
  
imports: import abc
  from collections.abc import Sequence
  import inspect
  from typing import Any, Optional
  from lit_nlp.api import dataset
  from lit_nlp.api import model
  from lit_nlp.api import types
label_desc: Use image node_id 2 for calling the Annotator obj's underlying member method code with example usage: obj.annotate(inputs, dataset, dataset_spec_to_annotate) without return types