    def text_to_instance(self, *inputs) -> Instance:
        """
        Does whatever tokenization or processing is necessary to go from textual input to an
        `Instance`.  The primary intended use for this is with a
        :class:`~allennlp.predictors.predictor.Predictor`, which gets text input as a JSON
        object and needs to process it to be input to a model.

        The intent here is to share code between :func:`_read` and what happens at
        model serving time, or any other time you want to make a prediction from new data.  We need
        to process the data in the same way it was done at training time.  Allowing the
        `DatasetReader` to process new text lets us accomplish this, as we can just call
        `DatasetReader.text_to_instance` when serving predictions.

        The input type here is rather vaguely specified, unfortunately.  The `Predictor` will
        have to make some assumptions about the kind of `DatasetReader` that it's using, in order
        to pass it the right information.
        """
        raise NotImplementedError
Does whatever tokenization or processing is necessary to go from textual input to an
`Instance`.  The primary intended use for this is with a
:class:`~allennlp.predictors.predictor.Predictor`, which gets text input as a JSON
object and needs to process it to be input to a model.

The intent here is to share code between :func:`_read` and what happens at
model serving time, or any other time you want to make a prediction from new data.  We need
to process the data in the same way it was done at training time.  Allowing the
`DatasetReader` to process new text lets us accomplish this, as we can just call
`DatasetReader.text_to_instance` when serving predictions.

The input type here is rather vaguely specified, unfortunately.  The `Predictor` will
have to make some assumptions about the kind of `DatasetReader` that it's using, in order
to pass it the right information.
allennlp/data/dataset_readers/dataset_reader.py