def METHOD_NAME(context_batch):
    """Preprocesses the context batch by combining previous and current utterances.
    Args:
      context_batch (list): List of conversation contexts.
    Returns:
      list: Preprocessed context batch.
    """
    optimized_context_batch = []
    for hist_uttr in context_batch:
        if len(hist_uttr) == 1:
            optimized_context_batch.append(hist_uttr[0])
        else:
            prev_uttr = hist_uttr[-2]
            cur_uttr = hist_uttr[-1]
            is_q = (
                any([prev_uttr.startswith(q_word) for q_word in ["what ", "who ", "when ", "where "]])
                or "?" in prev_uttr
            )
            if is_q and len(cur_uttr.split()) < 3:
                optimized_context_batch.append(f"{prev_uttr} {cur_uttr}")
            else:
                optimized_context_batch.append(cur_uttr)
    return optimized_context_batch