class_docstr: Question Answering in Context (QuAC) is a dataset for modeling, understanding, and  participating in information seeking dialog.
class_docstr_tok: ["Question","Answering","in","Context","(","QuAC",")","is","a","dataset","for","modeling",",","understanding",",","and","participating","in","information","seeking","dialog","."]
code: def _generate_examples(self, filepath, split):
      with open(filepath, encoding="utf-8") as f:
          data = json.load(f)["data"]
          key = 0
          for row in data:
              paragraph = row["paragraphs"][0]["context"].replace(
                  "CANNOTANSWER", ""
              )
              qas = row["paragraphs"][0]["qas"]
              qa_pairs = [
                  (qa["question"], qa["answers"][0]["text"])
                  for qa in qas
              ]
              for question, answer in qa_pairs:
                  # Yields examples as (key, example) tuples
                  yield key, {
                      "title": row["title"],
                      "section_title": row["section_title"],
                      "paragraph": paragraph,
                      "question": question,
                      "answer": answer,
                  }
                  key += 1
  
imports: import json
  import datasets
label_desc: Use image node_id 3 for calling the Quac obj's underlying member method code with example usage: obj._generate_examples(filepath, split) without return types