class_docstr: Predictor for any model that takes in a sentence and returns
  a single set of tags for it.  In particular, it can be used with
  the [`CrfTagger`](https://docs.allennlp.org/models/main/models/tagging/models/crf_tagger/)
  model and also the [`SimpleTagger`](../models/simple_tagger.md) model.
  
  Registered as a `Predictor` with name "sentence_tagger".
docstr: Expects JSON that looks like `{"sentence": "..."}`.
  Runs the underlying model, and adds the `"words"` to the output.
docstr_tok: ["Expects","JSON","that","looks","like","`","{","``","sentence","''",":","``","...","''","}","`",".","Runs","the","underlying","model",",","and","adds","the","`","``","words","''","`","to","the","output","."]
code: def _json_to_instance(self, json_dict: JsonDict) -> Instance:
      """
      Expects JSON that looks like `{"sentence": "..."}`.
      Runs the underlying model, and adds the `"words"` to the output.
      """
      sentence = json_dict["sentence"]
      tokens = self._tokenizer.tokenize(sentence)
      return self._dataset_reader.text_to_instance(tokens)
  
file_path: allennlp/allennlp/predictors/sentence_tagger.py
imports: from typing import List, Dict
  import numpy
  from allennlp.common.util import JsonDict
  from allennlp.data import DatasetReader, Instance
  from allennlp.data.fields import FlagField, TextField, SequenceLabelField
  from allennlp.data.tokenizers.spacy_tokenizer import SpacyTokenizer
  from allennlp.models import Model
  from allennlp.predictors.predictor import Predictor
label_desc: Use image node_id 3 for calling the SentenceTaggerPredictor obj's underlying member method code with example usage: obj._json_to_instance(json_dict) and returns: self